Package: superml 0.5.7
Manish Saraswat
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.
Authors:
superml_0.5.7.tar.gz
superml_0.5.7.tar.gz(r-4.5-noble)superml_0.5.7.tar.gz(r-4.4-noble)
superml_0.5.7.tgz(r-4.4-emscripten)superml_0.5.7.tgz(r-4.3-emscripten)
superml.pdf |superml.html✨
superml/json (API)
NEWS
# Install 'superml' in R: |
install.packages('superml', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/saraswatmks/superml/issues
Last updated 10 months agofrom:9a7ac179b1. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 15 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 15 2024 |
Exports:bm_25check_packageCounterCountVectorizerdotdotmatGridSearchCVkFoldMeanKMeansTrainerKNNTrainerLabelEncoderLMTrainerNBTrainernormalise1dnormalise2dRandomSearchCVRFTrainersmoothMeansort_indextestdataTfIdfVectorizerXGBTrainer
Dependencies:assertthatBHdata.tableMetricsR6RcppRcppArmadillo
How to use CountVectorizer in R ?
Rendered fromGuide-to-CountVectorizer.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2020-02-24
Started: 2020-02-19
How to use TfidfVectorizer in R ?
Rendered fromGuide-to-TfidfVectorizer.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-02-19
Started: 2020-02-19
Introduction to SuperML
Rendered fromintroduction.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-02-19
Started: 2018-12-30
Readme and manuals
Help Manual
Help page | Topics |
---|---|
BM25 Matching | bm_25 |
cla_train | cla_train |
Calculate count of values in a list or vector | Counter |
Count Vectorizer | CountVectorizer |
Dot product similarity in vectors | dot |
Dot product similarity between a vector and matrix | dotmat |
Grid Search CV | GridSearchCV |
kFoldMean Calculator | kFoldMean |
K-Means Trainer | KMeansTrainer |
K Nearest Neighbours Trainer | KNNTrainer |
Label Encoder | LabelEncoder |
Linear Models Trainer | LMTrainer |
Naive Bayes Trainer | NBTrainer |
normalise1d | normalise1d |
normalise2d | normalise2d |
Random Search CV | RandomSearchCV |
reg_train | reg_train |
Random Forest Trainer | RFTrainer |
smoothMean Calculator | smoothMean |
sort_index | sort_index |
TfIDF(Term Frequency Inverse Document Frequency) Vectorizer | TfIdfVectorizer |
Extreme Gradient Boosting Trainer | XGBTrainer |