Scala Machine Learning

Branch	Status	CodeCov
master
develop

Light Weight Scala Machine Learning Library

A very light weight Scala machine learning library that provide some basic ML algorithms in Scala. The repo is served as a algorithm gallery. Please enjoy and dive into the algorithm that you will like to learn in its basic level.

Dev-Environment

• Scala 2.13

• Sbt 2.1

This package includes

Classification :

• [x] Naive Bayesian Decision [Code] [Usage]

• [x] K-Nearest Neighborhood (KNN) [Code] [Usage]

• [x] Gaussian Process Classification [Code] [Usage]

• [x] Linear Classification [Code] [Usage]

• [x] Linear Support Vector Machine (linear-SVM) [Code] [Usage]

• [x] Perceptron [Code] [Usage]

• [x] Decision Tree [Code] [Usage]

• [x] Random Forest [Code] [Usage]

• [x] Extreme Learning Machine [Code] [Usage]

Boost :

• [x] Naive Boost [Code] [Usage]

• [x] Weighted Boost [Code] [Usage]

• [x] Gradient Boost [Code] [Usage]

Regression :

• [x] Multiple Linear Regression [Code] [Usage]

• [x] Multivariate Linear Regression - GD [Code] [Usage]

• [x] Stochastic Gradient Decent [Code] [Usage]

• [x] Regression Tree [Code] [Usage]

Clustering :

• [x] Hierarchical [Code] [Usage]

• [x] DBSCAN [Code] [Usage]

• [x] HDBSCAN [Code] [Usage]

• [x] BIRCH [Code] [Usage]

• [x] K-Means [Code] [Usage]

• [x] EM Cluster [Code] [Usage]

• [x] Density Peak Cluster [Code] [Usage]

Neural Net & Deep Learning :

• [x] Neural Network (NN) [Code] [Usage]

• [x] Restricted Boltzmann Machine (RBM) [Code] [Usage]

• [x] Deep Belief Network (DBN) [Code] [Usage]

• [x] Long Short-Term Memory (LSTM) [Code] [Usage]

• [x] Neural Turing Machine - Memory Searching Cognition [Code (in another Repo)]

Optimization :

• [x] Gene Algorithm (GA) [Code] [Usage]

• [x] Minimax [Code] [Usage]

• [x] Monte Carlo Tree Search (MCTS) [Code] [Usage]

• [x] Epsilon Greedy Search [Code] [Usage]

• [x] Upper Confidence Bound [Code] [Usage]

Reinforcement Learning :

• [x] Naive Feedback [Code] [Usage]

• [x] Q-Learning [Code] [Usage]

• [x] Q-Neural Learning [Code] [Usage]

• [x] Deep Q-Network (DQN) [Code] [Usage]

• [x] Dueling DQN (D-DQN) [Code] [Usage]

• [x] Asynchronous Advantage Actor-Critic (A3C) [Code] [Usage]

• [x] Prioritized Experience Replay (PER-DQN) [Code] [Usage]

Feature Analysis :

• [x] Student-T Test [Code] [Usage]

• [x] ANOVA [Code] [Usage]

• [x] Linear Discriminant Analysis [Code] [Usage]

• [x] Quadratic Discriminant Analysis [Code] [Usage]

Feature Transformation :

• [x] One Hot Encoding [Code] [Usage]

Abnormal Detection :

• [x] Isolation Tree [Code] [Usage]

• [x] Isolation Forest [Code] [Usage]

• [x] Random Cut Tree [Code] [Usage]

• [x] Random Cut Forest [Code] [Usage]

TODO

• [ ] Rainbow - Deep Reinforcement Learning

• [ ] Alpha-go Zero (MCTS-NN) - Deep Reinforcement Learning

• [ ] Neural Architect Search (NAS) - Neural Network & Deep Learning

Installation Process

1. Install sbt

2. Clone this project

Test

sbt test

Build Jar

sbt assembly