ML modules in SmartPredict

To help you complete your Machine Learning projects from end to end, SmartPredict studio provides the state-of-the-art of ML algorithms.

The ML modules are parameterizable at will and are insured to cover all the granularity of your projects.

Both Classifiers and Regressors belong to the family of tools used for Supervised Learning. This article resumes well the main differences between the two as well as their uses.

SmartPredict' s toolbox contains various ML modules, made of regressors and classifiers from decision tree regressor to XGBoost Regressor.

• Decision Tree Regressor

• KNeighbors Classifiers

• KNeighbors Regressor

• Linear Regressor

• Logistic Regressor

• MLP Regressor

• Naive Bayes

• Random Forest Classifier

• Random Forest Regressor

• Support Vector Classifier

• Support Vector Regressor

• XGBoost Classifier

• XGBoost Regressor

More information on supervised learning such as details on the Nearest Neighbors or Support Vector machines are well-documented in the official Sci-kit learn documentation .