Hello Traders, It's finally that time, I'm releasing my baby out into the world. Unreal Algo is the answer to the question you didn't know you were asking. It's for beginners and advanced traders alike. I've made the settings very customizable, but also easy to just jump right in. How it works: It uses tons of calculations, confirmations, and filters to bring...
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: ...
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...
LVQ-based Strategy (FX and Crypto) Description: Learning Vector Quantization (LVQ) can be understood as a special case of an artificial neural network, more precisely, it applies a winner-take-all learning-based approach. It is based on prototype supervised learning classification task and trains its weights through a competitive learning...
Multi-timeframe Strategy based on Logistic Regression algorithm Description: This strategy uses a classic machine learning algorithm that came from statistics - Logistic Regression (LR). The first and most important thing about logistic regression is that it is not a 'Regression' but a 'Classification' algorithm. The name itself is somewhat misleading....
Perceptron-based strategy Description: The Learning Perceptron is the simplest possible artificial neural network (ANN), consisting of just a single neuron and capable of learning a certain class of binary classification problems. The idea behind ANNs is that by selecting good values for the weight parameters (and the bias), the ANN can model the relationships...
This is a multi-timeframe version of the kNN-based strategy.
kNN-based Strategy (FX and Crypto) Description: This strategy uses a classic machine learning algorithm - k Nearest Neighbours (kNN) - to let you find a prediction for the next (tomorrow's, next month's, etc.) market move. Being an unsupervised machine learning algorithm, kNN is one of the most simple learning algorithms. To do a prediction of the next market...
Hello, this script is the correction of my bull script related to Forex. (Bull market) Old script : 4H was chosen as the time frame. Thus, larger pips are at our disposal and we benefit more from the hedge effect of the leverage. Commissions per trade have been removed to get more realistic commissions. Because every wrong trade deletes all the 1% position...
► How To Use This Indicator ? • New Intraday Trading Levels Will Be Generated At 09:30 AM (UTC +05:30) • Buy If 5 Minutes Candle Close Above '' BreakOut Buy Here '' Level. • Sell If 5 Minutes Candle Close Below '' BreakOut Sell Here '' Level. • Book Profits At Breakout Buy or BreakOut Sell Targets. • If 1st Call Target Hit , Then Do Not Trade More On That Day. •...
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...
WARNING: Experimental and incomplete. Script is open to development and will be developed. This is just version 1.0 STRUCTURE This script is trained according to the open, close, high and low values of the bars. It is tried to predict the future values of opening, closing, high and low values. A few simple codes were used to correlate expectation...
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...
Relativity Adaptive Stop-Loss is a stop-loss technique that uses the Relativity Autonomous Distribution Blocks algorithm. For detailed info about Relativity Autonomous Distribution Blocks : *** Features This structure is different from standard stop-losses. The base frame is based on "Market Adaptive Stop-Loss" script. For detailed information about...