Convert RDD of numpy matrices to Dataframes

Hello, I am trying out the MultilayerPerceptronClassifier and it takes only a dataframe in its train method. Now the problem is that I have a training RDD of labels (x,y) with x and y being matrices. X has dimensions (1,401) while y has dimensions (1,10). I need to convert the train RDD to

Need help with SVM

Hello, I am using linear SVM to train my model and generate a line through my data. However my model always predicts 1 for all the feature examples. Here is my code: print data_rdd.take(5) [LabeledPoint(1.0, [1.9643,4.5957]), LabeledPoint(1.0, [2.2753,3.8589]), LabeledPoint(1.0, [2.9781,4.5651]),

Plotting decision boundary in non-linear logistic regression

Hello, I am working with Logistic Regression on a non linear data and I want to plot a decision boundary using the data. I dont know how do I do it using the contour plot. Could someone help me out please. This is the code I have written: from pyspark.ml.classification import LogisticRegression

Re: Making more features in Logistic Regression

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Re: Making more features in Logistic Regression

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Making more features in Logistic Regression

Hello, I am trying to solve a problem of Logistic Regression using Spark. I am still a newbie to machine learning. I wanted to ask that if I have 2 features for logistic regression and if the features are non-linear (regularized logistic regression) do we have to make more features by considering