Simple Neural Network Transformed RSI Introduction The Simple Neural Network Transformed RSI (ɴɴᴛ ʀsɪ) stands out as a formidable tool for traders who specialize in lower timeframe trading. It is an innovative enhancement of the traditional RSI readings with simple neural network smoothing techniques. This unique blend results in fairly accurate signals,...
Introduction Esqvair's Neural Reversal Probability Indicator is the indicator that shows probability of reversal. Warning: This script should only be used on 1 minute chart. How to use When a signal appears (by default it is a green bar), a reversal should be expected. The signal appears when the indicator value >= Threshold. If you want more signals, you must...
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
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',...
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...
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) ...
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: ...
Hello, this script consists of training candlesticks with Artificial Neural Networks (ANN). In addition to the first series, candlesticks' bodies and wicks were also introduced as training inputs. The inputs are individually trained to find the relationship between the subsequent historical value of all candlestick values 1.(High,Low,Close,Open) The outputs...
Hi, this is the MACD version of the ANN BTC Multi Timeframe Script. The MACD Periods were approximated to the Golden Cross values. MACD Lengths : Signal Length = 25 Fast Length = 50 Slow Length = 200 Regards.
Hi all, this script was created as a result of ANN training in all time frames of bitcoin data. Trained data is built on Chris Moody's Sling Shot system. CM Sling Shot System : This system automatically generates the ANN output for all time periods. Therefore, it has multi-time-frame feature. Artificial Neural Networks training details: Average Errors...
NOTE: Experimental. Pinescript implementation of Decimal to Binary and Binary to Decimal that is intended for use in the development of a neural network proof of concept. Intended for use in as subcomponent in the development of a more complex/highly experimental prototype. Protection/logic for edge cases above 11111111/255 (8bits) is NOT implemented. ...
This script consists of converting the value of 1 gram and / or 1 ounce of gold according to the national currencies into a system with artificial neural networks. Why did I feel such a need? Even though the printed products in the market are digitally circulated, only precious metals are available in full or near full. Silver is difficult to carry because you...
In this script, I tried to fit deep learning series to 1 command system up to the maximum point. After selecting the ticker, select the instrument from the menu and the system will automatically turn on the appropriate ann system. Listed instruments with alternative tickers and error rates: WTI : West Texas Intermediate (WTICOUSD , USOIL , CL1! ) Average...
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...
This script trained with Brent Crude Oil data including 7 basic indicators and 12 Guppy Exponential Moving Averages . Details : Learning cycles: 1 Training error: 0.006591 ( Smaller than 0.01 ! ) AutoSave cycles: 100 Input columns: 19 Output columns: 1 Excluded columns: 0 Training example rows: 300 Validating example rows: 0 Querying example...
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...
This is a fractal version of my deep learning script for SPY In addition, buy and sell conditions may appear in bar colors in green and red. You can choose from the menu if you wish. Fractal codes do not belong to me. So I didn't put any license. You can use it as you want, you can change and modify. Regards.Noldo