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# mlpy Documentation

Homepage: https://mlpy.fbk.eu

Module author: mlpy Developers <albanese@fbk.eu>

Section author: Davide Albanese <albanese@fbk.eu>

`mlpy` is a high-performance Python package for predictive modeling. It makes extensive use of NumPy (http://scipy.org) to provide fast N-dimensional array manipulation and easy integration of C code. `mlpy` provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. The package includes tools to measure stability in sets of ranked feature lists.

`mlpy` is a project of the MPBA Research Unit at FBK, the Bruno Kessler Foundation in Trento, Italy (http://mpba.fbk.eu).

- Tutorial
  - A Simple Example
- Wavelet Transform
  - Extend data
  - Discrete Wavelet Transform
  - Undecimated Wavelet Transform
  - Continuous Wavelet Transform
- Imputing
  - Purify
  - KNN imputing
- Distance Computations
  - Dynamic Time Warping
  - Minkowski Distance
- Clustering
  - Hierarchical Clustering
  - k-means
  - k-medoids
- Kernels
  - Linear Kernel
  - Gaussian Kernel
  - Polynomial Kernel
- Supervised Classification
  - Support Vector Machines (SVMs)
  - K Nearest Neighbor (KNN)
  - Fisher Discriminant Analysis (FDA)
  - Spectral Regression Discriminant Analysis (SRDA)
  - Penalized Discriminant Analysis (PDA)
  - Diagonal Linear Discriminant Analysis (DLDA)
- Regression
  - Ordinary Least Squares and Ridge Regression
  - Kernel Ridge Regression
  - Least Angle Regression (LAR)
  - LASSO (LARS implementation)
  - Gradient Descent
- Feature Weighting
  - Classifier-derived methods
  - Iterative RELIEF (I-RELIEF)
  - Feature Weighting/Selection Yijun Sun08
  - Discrete Wavelet Transform based (DWT)
- Feature Ranking (Wrapper Methods)
- Resampling Methods
  - k-fold
  - Monte Carlo
  - Leave-one-out
  - All Combinations
  - Manual Resampling
  - Resampling File
- Metric Functions
- Feature List Analysis
  - Canberra Indicator
  - Borda Count, Extraction Indicator, Mean Position Indicator
- Data Management
  - Importing and exporting data
  - Normalization
- Miscellaneous
  - Confidence Interval
  - Peaks Detection
  - Functions from GSL
  - Other
- Tools
  - Landscaping and Parameter Tuning
  - Other Tools

Index

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