[
https://issues.apache.org/jira/browse/MAHOUT-696?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
XiaoboGu updated MAHOUT-696:
----------------------------
Attachment: MAHOUT-696.patch
This version has passed the following testes:
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --showperf
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior L1
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior L2
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior up
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior tp
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior ebp
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior tp --prioroption 2
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior ebp --prioroption 2
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior L1 --auc global
mahout trainAdaptiveLogistic --input donut.csv --output d:\\model1 --target
color --categories 2 --predictors x y --types numeric --threads 8 --passes 1000
--showperf --features 100 --skipperfnum 399 --prior L1 --auc grouped
mahout validateAdaptiveLogistic --input donut-test.csv --model d:\\model1 --auc
--confusion --scores
mahout runAdaptiveLogistic --input donut-test.csv --model d:\\model1 --output
d:\\scores.txt --idcolumn c
mahout runAdaptiveLogistic --input donut-test.csv --model d:\\model1 --output
d:\\scores1.txt --idcolumn c --maxscoreonly
> Command line program for AdaptiveLogiscticRegression
> ----------------------------------------------------
>
> Key: MAHOUT-696
> URL: https://issues.apache.org/jira/browse/MAHOUT-696
> Project: Mahout
> Issue Type: Improvement
> Components: Classification
> Affects Versions: 0.5
> Reporter: XiaoboGu
> Assignee: Ted Dunning
> Fix For: 0.6
>
> Attachments: MAHOUT-696.patch, MAHOUT-696.patch, MAHOUT-696.patch,
> MAHOUT-696.patch, MAHOUT-696.patch, mahout-696-r1.patch, mahout-696-r2.patch,
> mahout-696-r3.patch, mahout-696-r4.patch, mahout-696-r5.patch
>
>
> Suggested by Ted, I'll try to write a command line program for
> AdaptiveLogicticRegression, but as I am not familir with the algorithm, I'll
> try to write a prototype for the program from a Java developer's perspactive,
> hope anyone else will help with the details of the algorithm.
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