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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This Indicator aims to fill a gap within traditional Standard Deviation Analysis. Rather than its usual applications, this Indicator focuses on applying Standard Deviation within an Oscillator and likewise applying a Machine Learning approach to it. By doing so, we may hope to achieve an Adaptive Oscillator which can help display when the price is deviating from...

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Machine Learning: VWAP aims to use Machine Learning to Identify the best location to Anchor the VWAP at. Rather than using a traditional fixed length or simply adjusting based on a Date / Time; by applying Machine Learning we may hope to identify crucial areas which make sense to reset the VWAP and start anew. VWAP’s may act similar to a Bollinger Band in the...

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//First script I have published. Constructive criticism is welcome. // I hope this may be helpful to you. // Initially, I did this for myself as I was getting some odd results from the ta.change function. Turns out it was my error LOL. What a surprise! // Typical syntax: ta.change(source, value) // value doesn't need to be included. If it isn't, it will only...

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This Indicator, will rate multiple different lengths of RSIs to determine which RSI to RSI MA cross produced the highest profit within the lookback span. This ‘Optimal RSI’ is then passed back, and if toggled will then be thrown into a Machine Learning calculation. You have the option to Filter RSI and RSI MA’s within the Machine Learning calculation. What this...

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The SuperTrend is a very useful Indicator to display when trends have shifted based on the Average True Range (ATR). Its underlying ideology is to calculate the ATR using a fixed length and then multiply it by a factor to calculate the SuperTrend +/-. When the close crosses the SuperTrend it changes direction. This Strategy features the Traditional SuperTrend...

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Trend lines have always been a key indicator that may help predict many different types of price movements. They have been well known to create different types of formations such as: Pennants, Channels, Flags and Wedges. The type of formation they create is based on how the formation was created and the angle it was created. For instance, if there was a strong...

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Overview: MFI Heat Maps are a visually appealing way to display the values of 29 different MFIs at the same time while being able to make sense of it. Each plot within the Indicator represents a different MFI value. The higher you get up, the longer the length that was used for this MFI. This Indicator also features the use of Machine Learning to help balance...

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Overview: Support and Resistance is normally based upon Pivot Points and Highest Highs and Lowest Lows. Many times coders even incorporate Volume, RSI and other factors into the equation. However there may be a downside to doing a pure technical approach based on historical levels. We live in a time where Machine Learning is becoming more and more used; thus we...

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Overview: AI Momentum is a kernel function based momentum Indicator. It uses Rational Quadratics to help smooth out the Moving Averages, this may give them a more accurate result. This Indicator has 2 main uses, first it displays ‘Zones’ that help you visualize the potential movement areas and when the price is out of bounds (Overvalued or Undervalued). Secondly...

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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 Momentum Oscillator brings together the K-Nearest Neighbors (KNN) algorithm and the predictive strength of the Tactical Sector Indicator (TSI) Momentum. This unique oscillator not only uses the insights from TSI Momentum but also taps into the power of machine learning therefore being designed to give traders a more comprehensive view of...

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⚠️❗ Important Limitations: Due to the way this script is designed, it operates specifically under certain conditions: Stocks & Forex : Only compatible with timeframes of 8 hours and above ⏰ Crypto : Only works with timeframes starting from 4 hours and higher ⏰ ❗Please note that the script will not work on lower timeframes.❗ Feature Extraction : It begins by...

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⭕️Innovative trading indicator that utilizes a k-NN-inspired algorithmic approach alongside traditional Exponential Moving Averages (EMAs) for more nuanced analysis. While the algorithm doesn't actually employ machine learning techniques, it mimics the logic of the k-Nearest Neighbors (k-NN) methodology. The script takes into account the closest 'k' distances...

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Introduction: This script implements a comprehensive trading strategy that adheres to the established rules and guidelines of housing trading. It leverages advanced machine learning techniques and incorporates customised moving averages, including the Conceptive Price Moving Average (CPMA), to provide accurate signals for informed trading decisions in the housing...

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█ OVERVIEW A Lorentzian Distance Classifier (LDC) is a Machine Learning classification algorithm capable of categorizing historical data from a multi-dimensional feature space. This indicator demonstrates how Lorentzian Classification can also be used to predict the direction of future price movements when used as the distance metric for a novel implementation of...

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Library "MLExtensions" normalizeDeriv(src, quadraticMeanLength) Returns the smoothed hyperbolic tangent of the input series. Parameters: src : The input series (i.e., the first-order derivative for price). quadraticMeanLength : The length of the quadratic mean (RMS). Returns: nDeriv The normalized derivative of the input series. ...

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The goal of this script is honestly to help everyone learn about trading with bots and algos. At least, to get started. Level 1: 10 lines of code. learn to plot 2 moving averages on your chart. learn to create a signal from a crossover. learn the very basics of Pine Script algo.

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