<commit_before># MachineLearningLibrary
Implementations of various machine learning methods
## Models
Logistic Regression using iteratively-reweighted least squares, conjugate gradients, Broyden-Fletcher-Goldfarb-Shanno (bfgs), and batch stochastic gradient descent <br/>
Rosenblatt's Perceptron <br/>
Both Quadratic and Linear Discriminant Analysis <br/> 
Multinomial and Bernoulli Naive Bayes <br/>
Kernelized and standard k nearest neighbors algorithm <br/>
Classification and Regression Trees <br/>
## Dependencies
General: numpy, scipy, and scikit-learn </br>
Specific: Linear Models have the option of showing learning rates, so matplotlib and seaborn are needed
## Installation
Can install by using the command $ pip install LibML<commit_msg>Adding RandomForest<commit_after># MachineLearningLibrary
Implementations of various machine learning methods
## Models
Logistic Regression using iteratively-reweighted least squares, conjugate gradients, Broyden-Fletcher-Goldfarb-Shanno (bfgs), and batch stochastic gradient descent <br/>
Rosenblatt's Perceptron <br/>
Both Quadratic and Linear Discriminant Analysis <br/> 
Multinomial and Bernoulli Naive Bayes <br/>
Kernelized and standard k nearest neighbors algorithm <br/>
Classification and Regression Trees <br/>
Random Forest <br/>
## Dependencies
General: numpy, scipy, and scikit-learn </br>
Specific: Linear Models have the option of showing learning rates, so matplotlib and seaborn are needed
## Installation
Can install by using the command $ pip install LibML
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