Machine Learning library for python
This library implemented only with python and numpy
- Decision Tree(ID3)
- Gaussian NaiveBayes
- NaiveBayes
- KNN
- Neural Network(FNN)
- Logistic Regression
- Linear Regression
- DBSCAN
- Apriori
- Kmeans
- HierarchicalClustering
- SVM
- SVC (SVM classifier)
- HMM
- CRF
- Numpy
- Python 2 or 3
$ sudo pip install --upgrade pytrain
import numpy as np
from pytrain.NeuralNetwork import FNN
# Simple dataset
train_mat = [[0.12,0.25],[3.24,4.33],[0.14,0.45],[7.30,4.23]]
train_label = [[0,1],[1,0],[0,1],[1,0]]
test_a = [0.10,0.33]
test_b = [4.0,4.5]
# Train model (FNN)
hidden_layer = [3,2]
fnn = FNN(train_mat, train_label, hidden_layer)
fnn.fit(lr = 0.01, epoch = 2000, err_th = 0.001, batch_size = 4)
# Test model (FNN)
res_a = np.rint(fnn.predict(test_a))
res_b = np.rint(fnn.predict(test_b))
print("X %s => Y %s" % (test_a, res_a))
print("X %s => Y %s" % (test_b, res_b))
———————— output ————————
X [0.1, 0.33] => Y [ 0. 1.]
X [4.0, 4.5] => Y [ 1. 0.]
Fork this repository, and write your algorithm, pull request.
Don't forgot proper test code in test_pytrain.
Test code should be work successfully in below command.
$ python test.py
- Machine Learning in Action by Peter Harrington (2013)
- Pattern Recognition by Ohilseok (2008)
- Machine Learning to Deep Learning by Deepcumen (2015)
- Pattern Recognition and Machine Learning by Christopher M. Bishop (2006)
- Sequential Minimal Optimization for SVM by John C.Platt (1998)