Sklearn Naive Bayes interpretation for GO. The project was implemented as part of a service that works with GaussianNB.
go get github.com/MiXaiLL76/naivebayes
TRAIN in Python train.ipynb
TEST in Golang examples/main.go
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 |
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 |