/machine_learing_algo_python

implement the machine learning algorithms by python for studying

Primary LanguagePython

Contents

Supervised Learning

neural network algorithm including following components
layers: conv1d, conv2d, mean pool, max pool, drop out, batch normalization, rnn, flatten, dense, tanh, relu
loss: binary crossentropy, categorical crossentropy, mse, categorical_hinge

Classification

perceptron algorithm
pocket algorithm
logistic regression algorithm including gradient descent, newton
softmax regression algorithm
learning vector quantization algorithm
k-NearestNeighbor algorithm
gaussian discriminant analysis algorithm
support vector machine algorithm including following components
kernel: linear, rbf
solver: smo, quadratic programming
discrete adaboost algorithm
real adaboost algorithm
gentle adaboost algorithm
naive bayesian algorithm for text classification
decision tree id3 algorithm
decision tree c45 algorithm

Regression

linear regression algorithm including gradient descent, newton, equation
locally weight linear regression algorithm
collaborative filtering algorithm

Classification and Regression

rbf network algorithm
decision tree cart algorithm
random_forest algorithm including bagging, random features, oob verification, feature selection
gradient boost decision tree algorithm

Dimensionality Reduction

linear discriminant analysis algorithm with "eigen" solver

Unsupervised Learning

Clustering

k-means algorithm
k-means++ algorithm
bisecting k-means algorithm
k-median algorithm
k-mediods algorithm
fuzzy c means algorithm
gaussian mixed model algorithm
agnes clustering algorithm
diana clustering algorithm
dbscan clustering algorithm
spectral clustering algorithm

Dimensionality Reduction

principal Component Analysis algorithm including whiten, zero-phase component analysis whiten, kernel pca
mltidimensional scaling algorithm
locally linear embedding algorithm

abnormal detection

support vector data description algorithm
isolate forest algorithm

Others

independent component analysis algorithm

Tools

image preprocess algorithms including rgb2gray, histogram of oriented gradient
text preprocess algorithms including tf-idf
distance algorithms including euclidean distance, manhattan distance, chebyshev distance, mahalanobis distance, cosine distance
kernel function including linear, rbf
preprocess algorithm including min-max scaler, z-score scaler, one-hot encoder, bagging
regularizer algorithm including L1, L2, elastic-net
scores including accuracy, precision, recall, f-score, R2 score, confusion matrix, pr curve, roc curve, auc, silhouette coefficient, 2d feature scatter, learning curve, information value
optimizer algorithm including following components
gradient descent: momentum,nesterov, adagrad,rmsprop,adam
weights initialization algorithm