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+<!DOCTYPE HTML>
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+ <title>Data preparation · Hivemall User Manual</title>
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+ <div class="book-summary">
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+ <input type="text" placeholder="Type to search" />
+</div>
+
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+ <nav role="navigation">
+
+
+
+<ul class="summary">
+
+
+
+
+ <li>
+ <a href="http://hivemall.incubator.apache.org/"; target="_blank"
class="custom-link"><i class="fa fa-home"></i> Home</a>
+ </li>
+
+
+
+
+ <li class="divider"></li>
+
+
+
+
+ <li class="header">TABLE OF CONTENTS</li>
+
+
+
+ <li class="chapter " data-level="1.1" data-path="../">
+
+ <a href="../">
+
+
+ <b>1.1.</b>
+
+ Introduction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2" data-path="../getting_started/">
+
+ <a href="../getting_started/">
+
+
+ <b>1.2.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.2.1"
data-path="../getting_started/installation.html">
+
+ <a href="../getting_started/installation.html">
+
+
+ <b>1.2.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.2"
data-path="../getting_started/permanent-functions.html">
+
+ <a href="../getting_started/permanent-functions.html">
+
+
+ <b>1.2.2.</b>
+
+ Install as permanent functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.2.3"
data-path="../getting_started/input-format.html">
+
+ <a href="../getting_started/input-format.html">
+
+
+ <b>1.2.3.</b>
+
+ Input Format
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.3" data-path="../misc/funcs.html">
+
+ <a href="../misc/funcs.html">
+
+
+ <b>1.3.</b>
+
+ List of Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4" data-path="../tips/">
+
+ <a href="../tips/">
+
+
+ <b>1.4.</b>
+
+ Tips for Effective Hivemall
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.4.1"
data-path="../tips/addbias.html">
+
+ <a href="../tips/addbias.html">
+
+
+ <b>1.4.1.</b>
+
+ Explicit add_bias() for better prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.2"
data-path="../tips/rand_amplify.html">
+
+ <a href="../tips/rand_amplify.html">
+
+
+ <b>1.4.2.</b>
+
+ Use rand_amplify() to better prediction results
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.3"
data-path="../tips/rt_prediction.html">
+
+ <a href="../tips/rt_prediction.html">
+
+
+ <b>1.4.3.</b>
+
+ Real-time prediction on RDBMS
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.4"
data-path="../tips/ensemble_learning.html">
+
+ <a href="../tips/ensemble_learning.html">
+
+
+ <b>1.4.4.</b>
+
+ Ensemble learning for stable prediction
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.5"
data-path="../tips/mixserver.html">
+
+ <a href="../tips/mixserver.html">
+
+
+ <b>1.4.5.</b>
+
+ Mixing models for a better prediction convergence (MIX
server)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.4.6" data-path="../tips/emr.html">
+
+ <a href="../tips/emr.html">
+
+
+ <b>1.4.6.</b>
+
+ Run Hivemall on Amazon Elastic MapReduce
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.5"
data-path="../tips/general_tips.html">
+
+ <a href="../tips/general_tips.html">
+
+
+ <b>1.5.</b>
+
+ General Hive/Hadoop Tips
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.5.1" data-path="../tips/rowid.html">
+
+ <a href="../tips/rowid.html">
+
+
+ <b>1.5.1.</b>
+
+ Adding rowid for each row
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.5.2"
data-path="../tips/hadoop_tuning.html">
+
+ <a href="../tips/hadoop_tuning.html">
+
+
+ <b>1.5.2.</b>
+
+ Hadoop tuning for Hivemall
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="1.6" data-path="../troubleshooting/">
+
+ <a href="../troubleshooting/">
+
+
+ <b>1.6.</b>
+
+ Troubleshooting
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="1.6.1"
data-path="../troubleshooting/oom.html">
+
+ <a href="../troubleshooting/oom.html">
+
+
+ <b>1.6.1.</b>
+
+ OutOfMemoryError in training
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.2"
data-path="../troubleshooting/mapjoin_task_error.html">
+
+ <a href="../troubleshooting/mapjoin_task_error.html">
+
+
+ <b>1.6.2.</b>
+
+ SemanticException generate map join task error: Cannot
serialize object
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.3"
data-path="../troubleshooting/asterisk.html">
+
+ <a href="../troubleshooting/asterisk.html">
+
+
+ <b>1.6.3.</b>
+
+ Asterisk argument for UDTF does not work
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.4"
data-path="../troubleshooting/num_mappers.html">
+
+ <a href="../troubleshooting/num_mappers.html">
+
+
+ <b>1.6.4.</b>
+
+ The number of mappers is less than input splits in Hadoop
2.x
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="1.6.5"
data-path="../troubleshooting/mapjoin_classcastex.html">
+
+ <a href="../troubleshooting/mapjoin_classcastex.html">
+
+
+ <b>1.6.5.</b>
+
+ Map-side join causes ClassCastException on Tez
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part II - Generic Features</li>
+
+
+
+ <li class="chapter " data-level="2.1"
data-path="../misc/generic_funcs.html">
+
+ <a href="../misc/generic_funcs.html">
+
+
+ <b>2.1.</b>
+
+ List of Generic Hivemall Functions
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.2" data-path="../misc/topk.html">
+
+ <a href="../misc/topk.html">
+
+
+ <b>2.2.</b>
+
+ Efficient Top-K Query Processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.3"
data-path="../misc/tokenizer.html">
+
+ <a href="../misc/tokenizer.html">
+
+
+ <b>2.3.</b>
+
+ Text Tokenizer
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="2.4" data-path="../misc/approx.html">
+
+ <a href="../misc/approx.html">
+
+
+ <b>2.4.</b>
+
+ Approximate Aggregate Functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part III - Feature Engineering</li>
+
+
+
+ <li class="chapter " data-level="3.1"
data-path="../ft_engineering/scaling.html">
+
+ <a href="../ft_engineering/scaling.html">
+
+
+ <b>3.1.</b>
+
+ Feature Scaling
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.2"
data-path="../ft_engineering/hashing.html">
+
+ <a href="../ft_engineering/hashing.html">
+
+
+ <b>3.2.</b>
+
+ Feature Hashing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.3"
data-path="../ft_engineering/selection.html">
+
+ <a href="../ft_engineering/selection.html">
+
+
+ <b>3.3.</b>
+
+ Feature Selection
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.4"
data-path="../ft_engineering/binning.html">
+
+ <a href="../ft_engineering/binning.html">
+
+
+ <b>3.4.</b>
+
+ Feature Binning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.5"
data-path="../ft_engineering/pairing.html">
+
+ <a href="../ft_engineering/pairing.html">
+
+
+ <b>3.5.</b>
+
+ Feature Paring
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.5.1"
data-path="../ft_engineering/polynomial.html">
+
+ <a href="../ft_engineering/polynomial.html">
+
+
+ <b>3.5.1.</b>
+
+ Polynomial features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.6"
data-path="../ft_engineering/ft_trans.html">
+
+ <a href="../ft_engineering/ft_trans.html">
+
+
+ <b>3.6.</b>
+
+ Feature Transformation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="3.6.1"
data-path="../ft_engineering/vectorization.html">
+
+ <a href="../ft_engineering/vectorization.html">
+
+
+ <b>3.6.1.</b>
+
+ Feature vectorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="3.6.2"
data-path="../ft_engineering/quantify.html">
+
+ <a href="../ft_engineering/quantify.html">
+
+
+ <b>3.6.2.</b>
+
+ Quantify non-number features
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="3.7"
data-path="../ft_engineering/tfidf.html">
+
+ <a href="../ft_engineering/tfidf.html">
+
+
+ <b>3.7.</b>
+
+ TF-IDF Calculation
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part IV - Evaluation</li>
+
+
+
+ <li class="chapter " data-level="4.1"
data-path="../eval/binary_classification_measures.html">
+
+ <a href="../eval/binary_classification_measures.html">
+
+
+ <b>4.1.</b>
+
+ Binary Classification Metrics
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.1.1" data-path="../eval/auc.html">
+
+ <a href="../eval/auc.html">
+
+
+ <b>4.1.1.</b>
+
+ Area under the ROC curve
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="4.2"
data-path="../eval/multilabel_classification_measures.html">
+
+ <a href="../eval/multilabel_classification_measures.html">
+
+
+ <b>4.2.</b>
+
+ Multi-label Classification Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.3"
data-path="../eval/regression.html">
+
+ <a href="../eval/regression.html">
+
+
+ <b>4.3.</b>
+
+ Regression Metrics
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.4" data-path="../eval/rank.html">
+
+ <a href="../eval/rank.html">
+
+
+ <b>4.4.</b>
+
+ Ranking Measures
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="4.5" data-path="../eval/datagen.html">
+
+ <a href="../eval/datagen.html">
+
+
+ <b>4.5.</b>
+
+ Data Generation
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="4.5.1"
data-path="../eval/lr_datagen.html">
+
+ <a href="../eval/lr_datagen.html">
+
+
+ <b>4.5.1.</b>
+
+ Logistic Regression data generation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part V - Supervised Learning</li>
+
+
+
+ <li class="chapter " data-level="5.1"
data-path="../supervised_learning/prediction.html">
+
+ <a href="../supervised_learning/prediction.html">
+
+
+ <b>5.1.</b>
+
+ How Prediction Works
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="5.2"
data-path="../supervised_learning/tutorial.html">
+
+ <a href="../supervised_learning/tutorial.html">
+
+
+ <b>5.2.</b>
+
+ Step-by-Step Tutorial on Supervised Learning
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part VI - Binary Classification</li>
+
+
+
+ <li class="chapter " data-level="6.1" data-path="general.html">
+
+ <a href="general.html">
+
+
+ <b>6.1.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2" data-path="a9a.html">
+
+ <a href="a9a.html">
+
+
+ <b>6.2.</b>
+
+ a9a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.2.1" data-path="a9a_dataset.html">
+
+ <a href="a9a_dataset.html">
+
+
+ <b>6.2.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.2" data-path="a9a_lr.html">
+
+ <a href="a9a_lr.html">
+
+
+ <b>6.2.2.</b>
+
+ Logistic Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.2.3" data-path="a9a_minibatch.html">
+
+ <a href="a9a_minibatch.html">
+
+
+ <b>6.2.3.</b>
+
+ Mini-batch gradient descent
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.3" data-path="news20.html">
+
+ <a href="news20.html">
+
+
+ <b>6.3.</b>
+
+ News20 Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.3.1"
data-path="news20_dataset.html">
+
+ <a href="news20_dataset.html">
+
+
+ <b>6.3.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.2" data-path="news20_pa.html">
+
+ <a href="news20_pa.html">
+
+
+ <b>6.3.2.</b>
+
+ Perceptron, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.3" data-path="news20_scw.html">
+
+ <a href="news20_scw.html">
+
+
+ <b>6.3.3.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.4"
data-path="news20_adagrad.html">
+
+ <a href="news20_adagrad.html">
+
+
+ <b>6.3.4.</b>
+
+ AdaGradRDA, AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.3.5" data-path="news20_rf.html">
+
+ <a href="news20_rf.html">
+
+
+ <b>6.3.5.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.4" data-path="kdd2010a.html">
+
+ <a href="kdd2010a.html">
+
+
+ <b>6.4.</b>
+
+ KDD2010a Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.4.1"
data-path="kdd2010a_dataset.html">
+
+ <a href="kdd2010a_dataset.html">
+
+
+ <b>6.4.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.4.2" data-path="kdd2010a_scw.html">
+
+ <a href="kdd2010a_scw.html">
+
+
+ <b>6.4.2.</b>
+
+ PA, CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.5" data-path="kdd2010b.html">
+
+ <a href="kdd2010b.html">
+
+
+ <b>6.5.</b>
+
+ KDD2010b Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.5.1"
data-path="kdd2010b_dataset.html">
+
+ <a href="kdd2010b_dataset.html">
+
+
+ <b>6.5.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.5.2" data-path="kdd2010b_arow.html">
+
+ <a href="kdd2010b_arow.html">
+
+
+ <b>6.5.2.</b>
+
+ AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.6" data-path="webspam.html">
+
+ <a href="webspam.html">
+
+
+ <b>6.6.</b>
+
+ Webspam Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="6.6.1"
data-path="webspam_dataset.html">
+
+ <a href="webspam_dataset.html">
+
+
+ <b>6.6.1.</b>
+
+ Data pareparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.6.2" data-path="webspam_scw.html">
+
+ <a href="webspam_scw.html">
+
+
+ <b>6.6.2.</b>
+
+ PA1, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="6.7" data-path="titanic_rf.html">
+
+ <a href="titanic_rf.html">
+
+
+ <b>6.7.</b>
+
+ Kaggle Titanic Tutorial
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8" data-path="criteo.html">
+
+ <a href="criteo.html">
+
+
+ <b>6.8.</b>
+
+ Criteo Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter active" data-level="6.8.1"
data-path="criteo_dataset.html">
+
+ <a href="criteo_dataset.html">
+
+
+ <b>6.8.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="6.8.2" data-path="criteo_ffm.html">
+
+ <a href="criteo_ffm.html">
+
+
+ <b>6.8.2.</b>
+
+ Field-Aware Factorization Machines
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VII - Multiclass Classification</li>
+
+
+
+ <li class="chapter " data-level="7.1"
data-path="../multiclass/news20.html">
+
+ <a href="../multiclass/news20.html">
+
+
+ <b>7.1.</b>
+
+ News20 Multiclass Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.1.1"
data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>7.1.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.2"
data-path="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest_dataset.html">
+
+
+ <b>7.1.2.</b>
+
+ Data preparation for one-vs-the-rest classifiers
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.3"
data-path="../multiclass/news20_pa.html">
+
+ <a href="../multiclass/news20_pa.html">
+
+
+ <b>7.1.3.</b>
+
+ PA
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.4"
data-path="../multiclass/news20_scw.html">
+
+ <a href="../multiclass/news20_scw.html">
+
+
+ <b>7.1.4.</b>
+
+ CW, AROW, SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.5"
data-path="../multiclass/news20_ensemble.html">
+
+ <a href="../multiclass/news20_ensemble.html">
+
+
+ <b>7.1.5.</b>
+
+ Ensemble learning
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.1.6"
data-path="../multiclass/news20_one-vs-the-rest.html">
+
+ <a href="../multiclass/news20_one-vs-the-rest.html">
+
+
+ <b>7.1.6.</b>
+
+ one-vs-the-rest classifier
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="7.2"
data-path="../multiclass/iris.html">
+
+ <a href="../multiclass/iris.html">
+
+
+ <b>7.2.</b>
+
+ Iris Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="7.2.1"
data-path="../multiclass/iris_dataset.html">
+
+ <a href="../multiclass/iris_dataset.html">
+
+
+ <b>7.2.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.2"
data-path="../multiclass/iris_scw.html">
+
+ <a href="../multiclass/iris_scw.html">
+
+
+ <b>7.2.2.</b>
+
+ SCW
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="7.2.3"
data-path="../multiclass/iris_randomforest.html">
+
+ <a href="../multiclass/iris_randomforest.html">
+
+
+ <b>7.2.3.</b>
+
+ Random Forest
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part VIII - Regression</li>
+
+
+
+ <li class="chapter " data-level="8.1"
data-path="../regression/general.html">
+
+ <a href="../regression/general.html">
+
+
+ <b>8.1.</b>
+
+ Regression
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2"
data-path="../regression/e2006.html">
+
+ <a href="../regression/e2006.html">
+
+
+ <b>8.2.</b>
+
+ E2006-tfidf Regression Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.2.1"
data-path="../regression/e2006_dataset.html">
+
+ <a href="../regression/e2006_dataset.html">
+
+
+ <b>8.2.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.2.2"
data-path="../regression/e2006_arow.html">
+
+ <a href="../regression/e2006_arow.html">
+
+
+ <b>8.2.2.</b>
+
+ Passive Aggressive, AROW
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="8.3"
data-path="../regression/kddcup12tr2.html">
+
+ <a href="../regression/kddcup12tr2.html">
+
+
+ <b>8.3.</b>
+
+ KDDCup 2012 Track 2 CTR Prediction Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="8.3.1"
data-path="../regression/kddcup12tr2_dataset.html">
+
+ <a href="../regression/kddcup12tr2_dataset.html">
+
+
+ <b>8.3.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.2"
data-path="../regression/kddcup12tr2_lr.html">
+
+ <a href="../regression/kddcup12tr2_lr.html">
+
+
+ <b>8.3.2.</b>
+
+ Logistic Regression, Passive Aggressive
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.3"
data-path="../regression/kddcup12tr2_lr_amplify.html">
+
+ <a href="../regression/kddcup12tr2_lr_amplify.html">
+
+
+ <b>8.3.3.</b>
+
+ Logistic Regression with amplifier
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="8.3.4"
data-path="../regression/kddcup12tr2_adagrad.html">
+
+ <a href="../regression/kddcup12tr2_adagrad.html">
+
+
+ <b>8.3.4.</b>
+
+ AdaGrad, AdaDelta
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part IX - Recommendation</li>
+
+
+
+ <li class="chapter " data-level="9.1" data-path="../recommend/cf.html">
+
+ <a href="../recommend/cf.html">
+
+
+ <b>9.1.</b>
+
+ Collaborative Filtering
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.1.1"
data-path="../recommend/item_based_cf.html">
+
+ <a href="../recommend/item_based_cf.html">
+
+
+ <b>9.1.1.</b>
+
+ Item-based collaborative filtering
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.2"
data-path="../recommend/news20.html">
+
+ <a href="../recommend/news20.html">
+
+
+ <b>9.2.</b>
+
+ News20 Related Article Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.2.1"
data-path="../multiclass/news20_dataset.html">
+
+ <a href="../multiclass/news20_dataset.html">
+
+
+ <b>9.2.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.2"
data-path="../recommend/news20_jaccard.html">
+
+ <a href="../recommend/news20_jaccard.html">
+
+
+ <b>9.2.2.</b>
+
+ LSH/MinHash and Jaccard similarity
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.3"
data-path="../recommend/news20_knn.html">
+
+ <a href="../recommend/news20_knn.html">
+
+
+ <b>9.2.3.</b>
+
+ LSH/MinHash and brute-force search
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.2.4"
data-path="../recommend/news20_bbit_minhash.html">
+
+ <a href="../recommend/news20_bbit_minhash.html">
+
+
+ <b>9.2.4.</b>
+
+ kNN search using b-Bits MinHash
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="9.3"
data-path="../recommend/movielens.html">
+
+ <a href="../recommend/movielens.html">
+
+
+ <b>9.3.</b>
+
+ MovieLens Movie Recommendation Tutorial
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="9.3.1"
data-path="../recommend/movielens_dataset.html">
+
+ <a href="../recommend/movielens_dataset.html">
+
+
+ <b>9.3.1.</b>
+
+ Data preparation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.2"
data-path="../recommend/movielens_cf.html">
+
+ <a href="../recommend/movielens_cf.html">
+
+
+ <b>9.3.2.</b>
+
+ Item-based collaborative filtering
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.3"
data-path="../recommend/movielens_mf.html">
+
+ <a href="../recommend/movielens_mf.html">
+
+
+ <b>9.3.3.</b>
+
+ Matrix Factorization
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.4"
data-path="../recommend/movielens_fm.html">
+
+ <a href="../recommend/movielens_fm.html">
+
+
+ <b>9.3.4.</b>
+
+ Factorization Machine
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.5"
data-path="../recommend/movielens_slim.html">
+
+ <a href="../recommend/movielens_slim.html">
+
+
+ <b>9.3.5.</b>
+
+ SLIM for fast top-k recommendation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="9.3.6"
data-path="../recommend/movielens_cv.html">
+
+ <a href="../recommend/movielens_cv.html">
+
+
+ <b>9.3.6.</b>
+
+ 10-fold cross validation (Matrix Factorization)
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part X - Anomaly Detection</li>
+
+
+
+ <li class="chapter " data-level="10.1" data-path="../anomaly/lof.html">
+
+ <a href="../anomaly/lof.html">
+
+
+ <b>10.1.</b>
+
+ Outlier Detection using Local Outlier Factor (LOF)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.2" data-path="../anomaly/sst.html">
+
+ <a href="../anomaly/sst.html">
+
+
+ <b>10.2.</b>
+
+ Change-Point Detection using Singular Spectrum
Transformation (SST)
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="10.3"
data-path="../anomaly/changefinder.html">
+
+ <a href="../anomaly/changefinder.html">
+
+
+ <b>10.3.</b>
+
+ ChangeFinder: Detecting Outlier and Change-Point
Simultaneously
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XI - Clustering</li>
+
+
+
+ <li class="chapter " data-level="11.1"
data-path="../clustering/lda.html">
+
+ <a href="../clustering/lda.html">
+
+
+ <b>11.1.</b>
+
+ Latent Dirichlet Allocation
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="11.2"
data-path="../clustering/plsa.html">
+
+ <a href="../clustering/plsa.html">
+
+
+ <b>11.2.</b>
+
+ Probabilistic Latent Semantic Analysis
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XII - GeoSpatial Functions</li>
+
+
+
+ <li class="chapter " data-level="12.1"
data-path="../geospatial/latlon.html">
+
+ <a href="../geospatial/latlon.html">
+
+
+ <b>12.1.</b>
+
+ Lat/Lon functions
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIII - Hivemall on Spark</li>
+
+
+
+ <li class="chapter " data-level="13.1"
data-path="../spark/getting_started/">
+
+ <a href="../spark/getting_started/">
+
+
+ <b>13.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.1.1"
data-path="../spark/getting_started/installation.html">
+
+ <a href="../spark/getting_started/installation.html">
+
+
+ <b>13.1.1.</b>
+
+ Installation
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.2"
data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.2.</b>
+
+ Binary Classification
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.2.1"
data-path="../spark/binaryclass/a9a_df.html">
+
+ <a href="../spark/binaryclass/a9a_df.html">
+
+
+ <b>13.2.1.</b>
+
+ a9a tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.2.2"
data-path="../spark/binaryclass/a9a_sql.html">
+
+ <a href="../spark/binaryclass/a9a_sql.html">
+
+
+ <b>13.2.2.</b>
+
+ a9a tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.3"
data-path="../spark/binaryclass/">
+
+ <a href="../spark/binaryclass/">
+
+
+ <b>13.3.</b>
+
+ Regression
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.3.1"
data-path="../spark/regression/e2006_df.html">
+
+ <a href="../spark/regression/e2006_df.html">
+
+
+ <b>13.3.1.</b>
+
+ E2006-tfidf regression tutorial for DataFrame
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.3.2"
data-path="../spark/regression/e2006_sql.html">
+
+ <a href="../spark/regression/e2006_sql.html">
+
+
+ <b>13.3.2.</b>
+
+ E2006-tfidf regression tutorial for SQL
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+ <li class="chapter " data-level="13.4"
data-path="../spark/misc/misc.html">
+
+ <a href="../spark/misc/misc.html">
+
+
+ <b>13.4.</b>
+
+ Generic features
+
+ </a>
+
+
+
+ <ul class="articles">
+
+
+ <li class="chapter " data-level="13.4.1"
data-path="../spark/misc/topk_join.html">
+
+ <a href="../spark/misc/topk_join.html">
+
+
+ <b>13.4.1.</b>
+
+ Top-k join processing
+
+ </a>
+
+
+
+ </li>
+
+ <li class="chapter " data-level="13.4.2"
data-path="../spark/misc/functions.html">
+
+ <a href="../spark/misc/functions.html">
+
+
+ <b>13.4.2.</b>
+
+ Other utility functions
+
+ </a>
+
+
+
+ </li>
+
+
+ </ul>
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - Hivemall on Docker</li>
+
+
+
+ <li class="chapter " data-level="14.1"
data-path="../docker/getting_started.html">
+
+ <a href="../docker/getting_started.html">
+
+
+ <b>14.1.</b>
+
+ Getting Started
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="header">Part XIV - External References</li>
+
+
+
+ <li class="chapter " data-level="15.1" >
+
+ <a target="_blank"
href="https://github.com/daijyc/hivemall/wiki/PigHome";>
+
+
+ <b>15.1.</b>
+
+ Hivemall on Apache Pig
+
+ </a>
+
+
+
+ </li>
+
+
+
+
+ <li class="divider"></li>
+
+ <li>
+ <a href="https://www.gitbook.com"; target="blank" class="gitbook-link">
+ Published with GitBook
+ </a>
+ </li>
+</ul>
+
+
+ </nav>
+
+
+ </div>
+
+ <div class="book-body">
+
+ <div class="body-inner">
+
+
+
+<div class="book-header" role="navigation">
+
+
+ <!-- Title -->
+ <h1>
+ <i class="fa fa-circle-o-notch fa-spin"></i>
+ <a href=".." >Data preparation</a>
+ </h1>
+</div>
+
+
+
+
+ <div class="page-wrapper" tabindex="-1" role="main">
+ <div class="page-inner">
+
+<div id="book-search-results">
+ <div class="search-noresults">
+
+ <section class="normal markdown-section">
+
+ <!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+<!-- toc --><div id="toc" class="toc">
+
+<ul>
+<li><a href="#download-data">Download data</a></li>
+<li><a href="#convert-data-into-csv-format">Convert data into CSV
format</a></li>
+<li><a href="#create-tables">Create tables</a></li>
+</ul>
+
+</div><!-- tocstop -->
+<h1 id="download-data">Download data</h1>
+<p>Get dataset of <a
href="https://www.kaggle.com/c/criteo-display-ad-challenge";
target="_blank">Kaggle Display Advertising Challenge</a> from one of the
following sources:</p>
+<ol>
+<li><a
href="http://labs.criteo.com/2014/02/kaggle-display-advertising-challenge-dataset/";
target="_blank">Original competition data</a> (by Criteo Labs) [~20GB]</li>
+<li><a href="http://labs.criteo.com/2014/02/dataset/"; target="_blank">Subset
of the original competition data</a> (by Criteo Labs) [~30MB]</li>
+<li><a href="https://github.com/guestwalk/kaggle-2014-criteo";
target="_blank">Tiny sample data</a> (by the winners of the competition)
[~20bytes]</li>
+</ol>
+<p>It should be noted that you must accept and agree with <strong>CRITEO LABS
DATA TERM OF USE</strong> before downloading the data.</p>
+<h1 id="convert-data-into-csv-format">Convert data into CSV format</h1>
+<p>Here, you can use a script prepared by one of the Hivemall PPMC members:
<strong><a href="https://github.com/takuti/criteo-ffm";
target="_blank">takuti/criteo-ffm</a></strong>.</p>
+<p>Clone the repository:</p>
+<pre><code class="lang-sh">git <span class="hljs-built_in">clone</span>
g...@github.com:takuti/criteo-ffm.git
+<span class="hljs-built_in">cd</span> criteo-ffm
+</code></pre>
+<p>A script <a href="https://github.com/takuti/criteo-ffm/blob/master/data.sh";
target="_blank"><code>data.sh</code></a> downloads the original data and
converts them into CSV format:</p>
+<pre><code class="lang-sh">./data.sh <span class="hljs-comment"># downloads
the original data and generates `train.csv` and `test.csv`</span>
+ln <span class="hljs-_">-s</span> train.csv tr.csv
+ln <span class="hljs-_">-s</span> test.csv te.csv
+</code></pre>
+<p>Or, since the original data is very huge, starting from the tiny sample
data bundled into the repository would be better:</p>
+<pre><code class="lang-sh">ln <span class="hljs-_">-s</span> train.tiny.csv
tr.csv
+ln <span class="hljs-_">-s</span> test.tiny.csv te.csv
+</code></pre>
+<h1 id="create-tables">Create tables</h1>
+<p>Load the CSV files to Hive tables as:</p>
+<pre><code class="lang-sh">hadoop fs -put tr.csv /criteo/train
+hadoop fs -put te.csv /criteo/<span class="hljs-built_in">test</span>
+</code></pre>
+<pre><code class="lang-sql"><span class="hljs-keyword">CREATE</span> <span
class="hljs-keyword">DATABASE</span> <span class="hljs-keyword">IF</span> <span
class="hljs-keyword">NOT</span> <span class="hljs-keyword">EXISTS</span> criteo;
+<span class="hljs-keyword">use</span> criteo;
+</code></pre>
+<pre><code class="lang-sql"><span class="hljs-keyword">DROP</span> <span
class="hljs-keyword">TABLE</span> <span class="hljs-keyword">IF</span> <span
class="hljs-keyword">EXISTS</span> train;
+<span class="hljs-keyword">CREATE</span> <span
class="hljs-keyword">EXTERNAL</span> <span class="hljs-keyword">TABLE</span>
train (
+ <span class="hljs-keyword">id</span> <span
class="hljs-built_in">bigint</span>,
+ label <span class="hljs-built_in">int</span>,
+ <span class="hljs-comment">-- quantitative features</span>
+ i1 <span class="hljs-built_in">int</span>,i2 <span
class="hljs-built_in">int</span>,i3 <span class="hljs-built_in">int</span>,i4
<span class="hljs-built_in">int</span>,i5 <span
class="hljs-built_in">int</span>,i6 <span class="hljs-built_in">int</span>,i7
<span class="hljs-built_in">int</span>,i8 <span
class="hljs-built_in">int</span>,i9 <span class="hljs-built_in">int</span>,i10
<span class="hljs-built_in">int</span>,i11 <span
class="hljs-built_in">int</span>,i12 <span class="hljs-built_in">int</span>,i13
<span class="hljs-built_in">int</span>,
+ <span class="hljs-comment">-- categorical features</span>
+ c1 <span class="hljs-keyword">string</span>,c2 <span
class="hljs-keyword">string</span>,c3 <span
class="hljs-keyword">string</span>,c4 <span
class="hljs-keyword">string</span>,c5 <span
class="hljs-keyword">string</span>,c6 <span
class="hljs-keyword">string</span>,c7 <span
class="hljs-keyword">string</span>,c8 <span
class="hljs-keyword">string</span>,c9 <span
class="hljs-keyword">string</span>,c10 <span
class="hljs-keyword">string</span>,c11 <span
class="hljs-keyword">string</span>,c12 <span
class="hljs-keyword">string</span>,c13 <span
class="hljs-keyword">string</span>,c14 <span
class="hljs-keyword">string</span>,c15 <span
class="hljs-keyword">string</span>,c16 <span
class="hljs-keyword">string</span>,c17 <span
class="hljs-keyword">string</span>,c18 <span
class="hljs-keyword">string</span>,c19 <span
class="hljs-keyword">string</span>,c20 <span
class="hljs-keyword">string</span>,c21 <span
class="hljs-keyword">string</span>,c22 <span
class="hljs-keyword">string</span>,c23 <span clas
s="hljs-keyword">string</span>,c24 <span
class="hljs-keyword">string</span>,c25 <span
class="hljs-keyword">string</span>,c26 <span class="hljs-keyword">string</span>
+) <span class="hljs-keyword">ROW</span> <span
class="hljs-keyword">FORMAT</span>
+<span class="hljs-keyword">DELIMITED</span> <span
class="hljs-keyword">FIELDS</span> <span class="hljs-keyword">TERMINATED</span>
<span class="hljs-keyword">BY</span> <span
class="hljs-string">','</span>
+<span class="hljs-keyword">STORED</span> <span class="hljs-keyword">AS</span>
TEXTFILE LOCATION <span class="hljs-string">'/criteo/train'</span>;
+</code></pre>
+<pre><code class="lang-sql"><span class="hljs-keyword">DROP</span> <span
class="hljs-keyword">TABLE</span> <span class="hljs-keyword">IF</span> <span
class="hljs-keyword">EXISTS</span> <span class="hljs-keyword">test</span>;
+<span class="hljs-keyword">CREATE</span> <span
class="hljs-keyword">EXTERNAL</span> <span class="hljs-keyword">TABLE</span>
<span class="hljs-keyword">test</span> (
+ label <span class="hljs-built_in">int</span>,
+ <span class="hljs-comment">-- quantitative features</span>
+ i1 <span class="hljs-built_in">int</span>,i2 <span
class="hljs-built_in">int</span>,i3 <span class="hljs-built_in">int</span>,i4
<span class="hljs-built_in">int</span>,i5 <span
class="hljs-built_in">int</span>,i6 <span class="hljs-built_in">int</span>,i7
<span class="hljs-built_in">int</span>,i8 <span
class="hljs-built_in">int</span>,i9 <span class="hljs-built_in">int</span>,i10
<span class="hljs-built_in">int</span>,i11 <span
class="hljs-built_in">int</span>,i12 <span class="hljs-built_in">int</span>,i13
<span class="hljs-built_in">int</span>,
+ <span class="hljs-comment">-- categorical features</span>
+ c1 <span class="hljs-keyword">string</span>,c2 <span
class="hljs-keyword">string</span>,c3 <span
class="hljs-keyword">string</span>,c4 <span
class="hljs-keyword">string</span>,c5 <span
class="hljs-keyword">string</span>,c6 <span
class="hljs-keyword">string</span>,c7 <span
class="hljs-keyword">string</span>,c8 <span
class="hljs-keyword">string</span>,c9 <span
class="hljs-keyword">string</span>,c10 <span
class="hljs-keyword">string</span>,c11 <span
class="hljs-keyword">string</span>,c12 <span
class="hljs-keyword">string</span>,c13 <span
class="hljs-keyword">string</span>,c14 <span
class="hljs-keyword">string</span>,c15 <span
class="hljs-keyword">string</span>,c16 <span
class="hljs-keyword">string</span>,c17 <span
class="hljs-keyword">string</span>,c18 <span
class="hljs-keyword">string</span>,c19 <span
class="hljs-keyword">string</span>,c20 <span
class="hljs-keyword">string</span>,c21 <span
class="hljs-keyword">string</span>,c22 <span
class="hljs-keyword">string</span>,c23 <span clas
s="hljs-keyword">string</span>,c24 <span
class="hljs-keyword">string</span>,c25 <span
class="hljs-keyword">string</span>,c26 <span class="hljs-keyword">string</span>
+) <span class="hljs-keyword">ROW</span> <span
class="hljs-keyword">FORMAT</span>
+<span class="hljs-keyword">DELIMITED</span> <span
class="hljs-keyword">FIELDS</span> <span class="hljs-keyword">TERMINATED</span>
<span class="hljs-keyword">BY</span> <span
class="hljs-string">','</span>
+<span class="hljs-keyword">STORED</span> <span class="hljs-keyword">AS</span>
TEXTFILE LOCATION <span class="hljs-string">'/criteo/test'</span>;
+</code></pre>
+<p><div id="page-footer" class="localized-footer"><hr><!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
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