Scikit-learn

Scikit-learn is an open source machine learning library for the Python programming language.It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Classification : Identifying to which category an object belongs to Applications: Spam detection, Image recognition. Algorithms: SVM, nearest neighbors, random forest.

Regression : Predicting a continuous-valued attribute associated with an object. Applications: Drug response, Stock prices. Algorithms: SVR, ridge regression.

Clustering :Automatic grouping of similar objects into sets. Applications: Customer segmentation, Grouping experiment outcomes. Algorithms: k-Means, spectral clustering, mean-shift.

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More Information on Predictive Analysis Process

Predictive Analytics Process Flow

For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.