This indicator is designed for traders and analysts who employ Machine Learning (ML) techniques for cross-validation in financial markets. The script visually segments a selected range of historical price data into splits and batches, helping in the assessment of model performance over different market conditions. User Theory In ML, cross-validation is a...

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Building upon the innovative foundations laid by Zeiierman's Machine Learning Momentum Index (MLMI), this variation introduces a series of refinements and new features aimed at bolstering the model's predictive accuracy and responsiveness. Licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), my...

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The script provided is a comprehensive illustration of how to implement and execute a simplistic Neural Network (NN) on TradingView using PineScript. It encompasses the entire workflow from data input, weight initialization, implicit neuron calculation, feedforward computation, backpropagation for weight adjustments, generating predictions, to visualizing the...

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The Relational Quadratic Kernel Channel (RQK-Channel-V) is designed to provide more valuable potential price extremes or continuation points in the price trend. Example: Usage: Lookback Window: Adjust the "Lookback Window" parameter to control the number of previous bars considered when calculating the Rational Quadratic Estimate. Longer windows capture...

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The Machine Learning Regression Trend tool uses random sample consensus (RANSAC) to fit and extrapolate a linear model by discarding potential outliers, resulting in a more robust fit. 🔶 USAGE The proposed tool can be used like a regular linear regression, providing support/resistance as well as forecasting an estimated underlying trend. Using RANSAC...

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I changed MACD formula to divergence of (MA26/MA12 - 1). And its make it more useful. Cuz: 1) comparability with all other coins with different prices. 2) fix small numbers in low price coines like shiba 3) making a good indicator like RSI to use it for optimization and ML/AI projects as a variable Most important thing about this indicator is that its...

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Library "WIPNNetwork" this is a work in progress (WIP) and prone to have some errors, so use at your own risk... let me know if you find any issues.. Method for a generalized Neural Network. network(x) Generalized Neural Network Method. Parameters: x : TODO: add parameter x description here Returns: TODO: add what function returns

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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',...

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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...

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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) ...

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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: ...

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Gm traders, i have been a python programmer for some years studying artificial intelligence for general purpose; after some time i finally decided to have a look at some finance related stuff and scripts. Moved by curiosity i've decided to make some but decisive modifications to a script i tried to use initially but without success: the LVQ machine learning...

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Hi, this script comes from the idea that Ricardo Santos' Minkovski Distance Function is transferred to the period as a factor. Minkowski distance is used as a percentage factor with the help of Relative Strength Index function. Minkowski Distance Function Script : And thus an adaptive MACD was created. This script can give much better results in more...

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This script is the my Dependent Variable Odd Generator script : with the Put / Call Ratio ( PCR ) appended, only for CBOE and the instruments connected to it. For CBOE this script is more accurate and faster than Dependent Variable Odd Generator. And the stagnant market odds are better and more realistic. Do not use for timeframe periods less than 1 day. Because...

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