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superml

Build Machine Learning Models Like Using Python's Scikit-Learn Library in R

The idea is to provide a standard interface to users who use both R and Python for building machine learning models. This package provides a scikit-learn's fit, predict interface to train machine learning models in R.

Functions (25)

CountVectorizer

Count Vectorizer

Counter

Calculate count of values in a list or vector

GridSearchCV

Grid Search CV

KMeansTrainer

K-Means Trainer

KNNTrainer

K Nearest Neighbours Trainer

LMTrainer

Linear Models Trainer

LabelEncoder

Label Encoder

NBTrainer

Naive Bayes Trainer

RFTrainer

Random Forest Trainer

RandomSearchCV

Random Search CV

TfIdfVectorizer

TfIDF(Term Frequency Inverse Document Frequency) Vectorizer

XGBTrainer

Extreme Gradient Boosting Trainer

bm25

Best Matching(BM25) - Deprecated

bm_25

BM25 Matching

check_package

Internal function

cla_train

cla_train

dot

Dot product similarity in vectors

dotmat

Dot product similarity between a vector and matrix

kFoldMean

kFoldMean Calculator

normalise1d

normalise1d

normalise2d

normalise2d

reg_train

reg_train

smoothMean

smoothMean Calculator

sort_index

sort_index

testdata

Internal function

superml

Build Machine Learning Models Like Using Python's Scikit-Learn Library in R

v0.5.3
GPL-3 | file LICENSE
Authors
Manish Saraswat [aut, cre]
Initial release

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