sklearn-porter

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Prediction for ExtraTree model differs from sklearn (tested for C model)

5

I was trying to implement the predict_proba function for an Extra Tree model when I realized that the result returned by the transpiled version of the model differed from the...

LambertAn

Can't test accuracy in python and exported java code gives bad accuracy!

13

Hi, I started using your code to port a random forest estimator, first off I can't call the porter.integrity_score() function cause I get the following error: ``` Traceback (most recent...

Gizmomens

RFC prediction are inconsistent when using `max_depth`

9

I have created a `RandomForestclassifier` in Python using `sklearn`. Now I convert the code to C using `sklearn-porter`. In around 10-20% of the cases the prediction of the transpiled code...

skjerns

Multilabel prediction

3

I am trying to use the Sklearn Porter to transform my multilabel randomforest Classifier into Javascript. But the transformed Classifier doesn't predict multiple label. Does the Sklearn Porter support multilabel...

DerMajeed

Decision tree classifier porter C code predicting index of classes not actual class

5

Attaching training data csv file where first column is target class to predict. I generated pickle file and using sklearn-porter command line i convert pickle file to C Code and...

vijaykilledar

C# support

2

Darius, are you fine with the idea to support C#? If so, I will go ahead whenever I have free time. I might also contribute on other parts when I'm...

bpfliegel

Export Matrix as Vector (SVM and maybe other Models)

1

Firstly, I wold like to thank the authors of the library, it is really useful. Most of Java Algebra libraries are based on 1D primitive arrays (probably other languages too)...

gobber

Error when exporting SVC fitted using sparse matrix

2

I have an svm/svc classifier trained using sparse matrix as follows: ``` from sklearn_porter import Porter from sklearn import svm # load data and train the classifier: clf = svm.SVC(C=1.0,...

AMR-KELEG

I have trained a multi-label DecisionTreeClassifier and when I ported the result is the following: ``` java public static int predict(double[] features) { int[] classes = new int[2]; if (features[11]

gustavoresque

MultiOutputClassifier not supported

2

ValueError: Currently the given estimator 'MultiOutputClassifier(estimator=MLPClassifier(activation='relu', alpha=0.0001, batch_size='auto', beta_1=0.9, beta_2=0.999, early_stopping=False, epsilon=1e-08, hidden_layer_sizes=1, learning_rate='constant', learning_rate_init=0.001, max_iter=1, momentum=0.9, nesterovs_momentum=True, power_t=0.5, random_state=None, shuffle=True, solver='adam', tol=0.0001, validation_fraction=0.1, verbose=False, warm_start=False), n_jobs=1)' isn't supported.

lpschaub