Machine Learning Trendlines Cluster Indicator MT4 Download – Free – [TFlab]

The Machine Learning Trendlines Clustering Indicator combines machine learning methods with technical analysis to automatically detect trendlines.

This indicator uses clustering algorithms to group price data and linear regression to draw the trendline of each cluster.

Specifications Table of the Machine Learning Trendlines Cluster Indicator

The table below describes the specifications of the Machine Learning Trendlines Cluster Indicator:

Machine Learning Trendlines Cluster Indicator at a Glance

The Machine Learning Trendlines Clustering Indicator is designed to automatically identify valid trendlines on the price chart.

Based on clustering of price data, this trading tool identifies points that fall within a common price or behavioral range and plots them.

Uptrend

Based on the AUD/USD 15-minute chart, the price touches the drawn trendline and bounces upwards.

Downtrend

According to the USD/CHF chart, the drawn trendline effectively acts as resistance, and the price turns downward upon touching it.

Settings of the Machine Learning Trendlines Clustering Indicator

The adjustable parameters of the Machine Learning Trendlines Cluster Indicator are as follows:

• Analysis Window Size: The time window for analysis, i.e., the number of candles under review
• Number of Lines/Clusters: The number of lines or clusters to be identified
• Maximum Iterations: Maximum number of algorithm iterations during calculation
• Enable Slope Filtering: Enable filtering based on line slope
• Filter Direction (true = below threshold, false = above): Filtering direction based on slope threshold
• Threshold Sensitivity Factor: Sensitivity factor of the threshold for filtering lines
• Line Thickness: Thickness of the plotted lines
• Upper Line Color: Color of upper or resistance lines
• Lower Line Color: Color of lower or support lines

Conclusion

The Machine Learning Trendlines Clustering Indicator is an intelligent tool for automatic detection of trendlines using clustering algorithms and linear regression.

By focusing on similar price data, this indicator delivers more meaningful and accurate trendlines compared to traditional methods.