Neuron class
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm. This class is suitable for prediction on time series.
Dependencies
Neuron class needs pandas and numpy to work propertly.
Example of usage
Consider Y are targets and X are inputs.
## LNUGD
neuron = LNUGD()
prediction = 1
yn, w, e, Wall, MSE = neuron.train(Y_train, X_train, epochs=2, prediction=prediction)
yn, w, Wall, MSE, e = neuron.countSerie(Y, X, logging=False, prediction=prediction)
QNULM
neuron = QNULM()
prediction = 1
yn, w, e, Wall, MSE = neuron.train(Y_train, X_train, epochs=10, prediction=prediction)
yn, w, MSE, e = neuron.countSerie(Y, X, logging=False, prediction=prediction)
RBF
neuron = RBF()
prediction = 1
neuron.train(Y_train, X_train, prediction=prediction)
yn = neuron.count(Y,X, logging=True, beta=0.01, prediction=prediction)
MLPGD
neuron = MLPGD()
prediction = 1
yn = neuron.count(Y_train, X_train, prediction=prediction, epochs=5)
yn = neuron.count(Y, X, prediction=prediction, epochs=1)
MLPELM
neuron = MLPELM()
prediction = 1
yn = neuron.count(Y_train, X_train, prediction = prediction, epochs = 10)
yn = neuron.count(Y, X, prediction = prediction)
MLPLMWL
neuron = MLPLMWL()
prediction = 1
yn = neuron.count(Y, X, learningWindow = 50, overLearn = 10, prediction = prediction)
Support me
If you find this useful, consider supporting independent open-source development and buy me a coffee.
141 Sep 11, 2022
1 Dec 18, 2021
60 Jan 03, 2023
13 Sep 15, 2022
84 Jan 03, 2023
108 Dec 27, 2022
176 Dec 28, 2022
2 Nov 17, 2022
81 Dec 03, 2022
11 Dec 26, 2022
2 Dec 26, 2021
202 Nov 18, 2022
48 Sep 30, 2022
1.5k Dec 17, 2022
8 Jul 13, 2022
26 Dec 12, 2022
4 Jul 20, 2022
9 Dec 14, 2022
4.5k Dec 31, 2022
5 Nov 23, 2022