Welcome to mlpy’s documentation!

Release:3.5 Date:Feb 26, 2020 Homepage:http://mlpy.sourceforge.net

Machine Learning PYthon (mlpy) is a high-performance Python library for predictive modeling.

This reference manual details functions, modules, and objects included in mlpy.

• Install
  • Download
  • Installing on *nix from source
  • Installing on Windows Xp/Vista/7 from binary installer
• Introduction
  • Conventions
• Tutorial
  • Tutorial 1 - Iris Dataset
• Linear Methods for Regression
  • Ordinary Least Squares
  • Ridge Regression
  • Partial Least Squares
  • Last Angle Regression (LARS)
  • Elastic Net
• Linear Methods for Classification
  • Linear Discriminant Analysis Classifier (LDAC)
  • Basic Perceptron
  • Elastic Net Classifier
  • Logistic Regression
  • Support Vector Classification
  • Diagonal Linear Discriminant Analysis (DLDA)
  • Golub Classifier
• Kernels
  • Kernel Functions
  • Kernel Classes
  • Functions
  • Centering in Feature Space
  • Make a Custom Kernel
• Non Linear Methods for Regression
  • Kernel Ridge Regression
  • Support Vector Regression
• Non Linear Methods for Classification
  • Parzen-based classifier
  • Support Vector Classification
  • Kernel Fisher Discriminant Classifier
  • k-Nearest-Neighbor
  • Classification Tree
  • Maximum Likelihood Classifier
• Support Vector Machines (SVMs)
  • Support Vector Machines from [LIBSVM]
  • Kernel Adatron
• Large Linear Classification from [LIBLINEAR]
• Cluster Analysis
  • Hierarchical Clustering
  • Memory-saving Hierarchical Clustering
  • k-means
• Algorithms for Feature Weighting
  • Iterative RELIEF
• Feature Selection
  • Recursive Feature Elimination
• Dimensionality Reduction
  • Linear Discriminant Analysis (LDA)
  • Spectral Regression Discriminant Analysis (SRDA)
  • Kernel Fisher Discriminant Analysis (KFDA)
  • Principal Component Analysis (PCA)
  • Fast Principal Component Analysis (PCAFast)
  • Kernel Principal Component Analysis (KPCA)
• Cross Validation
  • Leave-one-out and k-fold
  • Random Subsampling (aka MonteCarlo)
  • All Combinations
• Metrics
  • Classification
  • Regression
• A Set of Statistical Functions
• Canberra Distances and Stability Indicator of Ranked Lists
  • Canberra distance
  • Canberra Distance with Location Parameter
  • Canberra Stability Indicator
• Borda Count
• Find Peaks
• Dynamic Time Warping (DTW)
  • Standard DTW
  • Subsequence DTW
• Longest Common Subsequence (LCS)
  • Standard LCS
  • LCS for real series
• mlpy.wavelet - Wavelet Transform
  • Padding
  • Discrete Wavelet Transform
  • Undecimated Wavelet Transform
  • Continuous Wavelet Transform
• Short Guide to Centering and Scaling

Indices and tables

• Index
• Module Index
• Search Page