artificial_intelligence

PresentTrading

█ Introduction and How it is Different The AI Supertrend Strategy is a unique hybrid approach that employs both traditional technical indicators and machine learning techniques. Unlike standard strategies that rely solely on traditional indicators or mathematical models, this strategy integrates the power of k-Nearest Neighbors (KNN), a machine learning...

RicardoSantos Wizard Zaktualizowano 

Library "FunctionNNLayer" Generalized Neural Network Layer method. function(inputs, weights, n_nodes, activation_function, bias, alpha, scale) Generalized Layer.   Parameters:      inputs : float array, input values.      weights : float array, weight values.      n_nodes : int, number of nodes in layer.      activation_function : string, default='sigmoid',...

RicardoSantos Wizard

Library "FunctionNNPerceptron" Perceptron Function for Neural networks. function(inputs, weights, bias, activation_function, alpha, scale) generalized perceptron node for Neural Networks.   Parameters:      inputs : float array, the inputs of the perceptron.      weights : float array, the weights for inputs.      bias : float, default=1.0, the default bias...

RicardoSantos Wizard Zaktualizowano 

Library "MLActivationFunctions" Activation functions for Neural networks. binary_step(value) Basic threshold output classifier to activate/deactivate neuron.   Parameters:      value : float, value to process.   Returns: float linear(value) Input is the same as output.   Parameters:      value : float, value to process.   Returns: float sigmoid(value) ...

RicardoSantos Wizard

Library "MLLossFunctions" Methods for Loss functions. mse(expects, predicts) Mean Squared Error (MSE) " MSE = 1/N * sum ((y - y')^2) ".   Parameters:      expects : float array, expected values.      predicts : float array, prediction values.   Returns: float binary_cross_entropy(expects, predicts) Binary Cross-Entropy Loss (log).   Parameters:     ...

LonesomeTheBlue Wizard Zaktualizowano 

Hello Traders/Programmers, For long time I thought that if it's possible to make a script that has own memory and criterias in Pine. it would learn and find patterns as images according to given criterias. after we have arrays of strings, lines, labels I tried and made this experimental script. The script works only for Long positions. Now lets look at how it...

Noldo

This script created by training WTI 4 hour data , 7 indicators and 12 Guppy Exponential Moving Averages. Details : Learning cycles: 1 AutoSave cycles: 100 Training error: 0.007593 ( Smaller than average target ! ) Input columns: 19 Output columns: 1 Excluded columns: 0 Training example rows: 300 Validating example rows: 0 Querying example rows: 0 Excluded...

Noldo

This script is formed by training the S & P 500 Index with various indicators. Details : Learning cycles: 78089 AutoSave cycles: 100 Training error: 0.011650 (Far less than the target, but acceptable.) Input columns: 19 Output columns: 1 Excluded columns: 0 Training example rows: 300 Validating example rows: 0 Querying example rows: 0 Excluded...

Noldo

This script is the 2nd version of the BTC Deep Learning (ANN) system. Created with the following indicators and tools: RSI MACD MOM Bollinger Bands Guppy Exponential Moving Averages: (3,5,8,10,12,15,30,35,40,45,50,60) Note: I was inspired by the CM Guppy Ema script. Thank you very much to dear wroclai for his great help. He has been a big help in the deep...