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GaussianNB Predictor ONLY. From sklearn to GO

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Description

Sklearn Naive Bayes interpretation for GO. The project was implemented as part of a service that works with GaussianNB.

Install

go get github.com/MiXaiLL76/naivebayes

Example

TRAIN in Python train.ipynb
TEST in Golang examples/main.go

Implementing Naive Bayes Classes

GaussianNB sklearn

Method Description Status
fit(X, y[, sample_weight]) Fit Gaussian Naive Bayes according to X, y W.I.P.
get_weight() Get weight for this estimator. ✓ DONE
set_weight(weight) Set the weight of this estimator. ✓ DONE
predict(X) Perform classification on an array of test vectors X. ✓ DONE
predict_log_proba(X) Return log-probability estimates for the test vector X. ✓ DONE
predict_proba(X) Return probability estimates for the test vector X. ✓ DONE
score(X, y[, sample_weight]) Return the mean accuracy on the given test data and labels. ✓ DONE

Utility

Method Description Status
argmax(array []float64) Returns the indices of the maximum values ✓ DONE
logsumexp(array []float64) Compute the log of the sum of exponentials of input elements. ✓ DONE
getShape(array [][]float64) Return the shape of an array. ✓ DONE
AccuracyScore(y_true, y_pred) Accuracy classification score. ✓ DONE

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GaussianNB Predictor ONLY. From sklearn to GO

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