PINE LIBRARY

MLPivotsBreakouts

By tkarolak
Updated
Library "MLPivotsBreakouts"
Utilizes k-NN machine learning to predict breakout zones from pivot points, aiding traders in identifying potential bullish and bearish market movements. Ideal for trend-following and breakout strategies.

breakouts(source, pivotBars, numNeighbors, maxData, predictionSmoothing)
  Parameters:
    source (float): series float: Price data for analysis.
    pivotBars (int): int: Number of bars for pivot point detection.
    numNeighbors (int): int: Neighbors count for k-NN prediction.
    maxData (int): int: Maximum pivot data points for analysis.
    predictionSmoothing (int): int: Smoothing period for predictions.
return [series float, series float, series int]: Lower and higher prediction bands plus pivot signal, 1 for ph and -1 for pl.
Release Notes
v2

Updated: Compiler annotations
Release Notes
v3

Updated:
breakouts(pivotBars, numNeighbors, maxData, predictionSmoothing)
  Detects and predicts breakout points from pivot data.
  Parameters:
    pivotBars (int): int: Number of bars for pivot point detection.
    numNeighbors (int): int: Neighbors count for k-NN prediction.
    maxData (int): int: Maximum pivot data points for analysis.
    predictionSmoothing (int): int: Smoothing period for predictions.
  Returns: [series float, series float, series int]: Lower and higher prediction bands plus pivot signal, 1 for ph and -1 for pl.
techindicator
tkarolak

Pine library

In true TradingView spirit, the author has published this Pine code as an open-source library so that other Pine programmers from our community can reuse it. Cheers to the author! You may use this library privately or in other open-source publications, but reuse of this code in a publication is governed by House rules.

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