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.
22 Dec 08, 2022
170 Dec 26, 2022
50 Dec 27, 2022
381 Dec 22, 2022
2k Dec 29, 2022
37 Oct 21, 2022
6 May 27, 2022
305 Dec 30, 2022
24 Dec 05, 2022
2 Jan 28, 2022
51 Nov 22, 2022
11 May 02, 2022
1k Jan 04, 2023
607 Dec 31, 2022
45 Dec 26, 2022
7 Apr 08, 2022
6 Oct 25, 2020
27 Nov 23, 2022
93 Nov 06, 2022
102 Oct 06, 2022