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mlpy provides a wide range of state-of-the-art machine learning methods for supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability and efficiency.
Category
Data Mining Software Free
Features
•Python method for machine learning •Provides high-level functions and classes •Works with Python 2 and 3 •Open Source •Compatible with PyInstaller
License
Open Source
Price
Free
Pricing
Subscription
Free Trial
Available
Users Size
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
•Python method for machine learning •Provides high-level functions and classes •Works with Python 2 and 3 •Open Source
What are the benefits?
• Provides a wide range of machine learning methods • Perform many statistical analyses • Easy to manipulate data • Open-source: free to download, use, extend • Access to online/PDF documentation
PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
8.3
Features & Functionality
7.6
7.0
Advanced Features
7.6
8.3
Integration
7.6
8.3
Performance
7.6
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Customer Support
7.6
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Implementation
—
Renew & Recommend
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Bottom Line
mlpy is multiplatform, it works with Python 2 and 3 and it is Open Source, distributed under the GNU General Public License version 3.
7.6
Editor Rating
8.0
Aggregated User Rating
3 ratings
You have rated this
Mlpy know as Machine Learning Python represents a python method for machine learning built on top of NumPy/SciPy (Python-based ecosystem of open-source software for mathematics, science, and engineering) and the GNU Scientific Libraries (represents numerical library for C and C++ programmers where a wide range of mathematical routines such as random number generators, special functions and least-squares fitting are provided).
Wide range of state-of-the-art machine learning methods are provided for supervised and unsupervised problems and mlpy is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability and efficiency. It provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, and clustering and feature selection.
This platform works with Python 2 and 3 and it is Open Source which means that it is distributed under the GNU General Public License version 3 and it is free. This platform has several features such as: regression that contains - least squares, ridge regression, last angle regression, elastic net, kernel ridge regression, support vector machines (SVR), partial least squares (PLS); classification - Linear Discriminant Analysis (LDA).
Advanced machine learning methods of supervised and unsupervised problems
Company size
Enterprise (>1001)
User Role
IT Support
User Industry
Financial services
Rating
Ease of use8.3
Features & Functionality8.2
Advanced Features8.3
Integration8.3
ADDITIONAL INFORMATION mlpy is a Python module for Machine learning built on top of NumPy/SciPy and the GNU scientific libraries. It is open source software distributed under the GNU General Public License. mlpy provides a variety of advanced machine learning methods of supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability, and efficiency. mlpy allows users to perform linear regression analysis including least squares, partial least squares, ridge regression, last angle regression, elastic net, kernel ridge regression, and support vector machines (SVR). You can also perform linear classification which entails the following features; Linear Discriminant Analysis (LDA), Basic Perceptron, Elastic Net, Logistic Regression, (Kernel) Support Vector Machines (SVM), Diagonal Linear Discriminant Analysis (DLDA), Golub Classifier, Parzen-based, (kernel) Fisher Discriminant Classifier k-Nearest-Neighbor, Iterative RELIEF, Classification Tree, and Maximum Likelihood Classifier. mlpy lets users manipulate data and perform clustering operations on it using these methods; hierarchical clustering, memory-saving hierarchical clustering, and k-means method. mlpy provides online documentation and reference manual that detail the functions, modules, and objects included in mlpy.
Advanced machine learning methods of supervised and unsupervised problems
Enterprise (>1001)
IT Support
Financial services
ADDITIONAL INFORMATION
mlpy is a Python module for Machine learning built on top of NumPy/SciPy and the GNU scientific libraries. It is open source software distributed under the GNU General Public License. mlpy provides a variety of advanced machine learning methods of supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability, and efficiency. mlpy allows users to perform linear regression analysis including least squares, partial least squares, ridge regression, last angle regression, elastic net, kernel ridge regression, and support vector machines (SVR). You can also perform linear classification which entails the following features; Linear Discriminant Analysis (LDA), Basic Perceptron, Elastic Net, Logistic Regression, (Kernel) Support Vector Machines (SVM), Diagonal Linear Discriminant Analysis (DLDA), Golub Classifier, Parzen-based, (kernel) Fisher Discriminant Classifier k-Nearest-Neighbor, Iterative RELIEF, Classification Tree, and Maximum Likelihood Classifier. mlpy lets users manipulate data and perform clustering operations on it using these methods; hierarchical clustering, memory-saving hierarchical clustering, and k-means method. mlpy provides online documentation and reference manual that detail the functions, modules, and objects included in mlpy.