VanillaML

VanillaML contains a collection of popular machine learning algorithms in Python. The implementations follow scikit-learn's API conventions and are made to be as simple as possible.

Demos

KMeans clustering.

Fitting the curve x*sin(x) using Gradient Boosted Trees.

Requirements

• Python 2.7
• Numpy and matplotlib which can be installed via:

$ sudo pip install -r requirements.txt

Learning algorithms

1. Supervised

• Classification

  • Nearest Neighbors
  • Naive Bayes
  • Perceptron
  • Linear Support Vector Machines
  • Logistic Regression
  • Maximum Entropy
  • Decision Trees
  • Random Forest
  • Feed-forward Neural Network
  • AdaBoost

• Regression

  • Nearest Neighbors
  • Linear Regression
  • Decision Trees
  • Random Forest
  • Feed-forward Neural Network
  • Gradient Boosting

• Ranking

  • RankNet
  • Linear RankSVM

2. Unsupervised

• Clustering
  • K-Means
• Decomposition
  • PCA

License

BSD