Machine Learning in Trading Strategy Design › Key Parameters
Michael BrenndoerferJanuary 3, 20261 min read
Quantitative FinanceAll chapters Part 13 of 15Machine Learning and Alternative Data
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The key parameters for unsupervised market structure models are:
- n_clusters: The number of groups to find in K-Means clustering. This determines the granularity of the resulting asset universe.
- contamination: The expected proportion of anomalies in the dataset for Isolation Forest. This sets the threshold for flagging data points as outliers.
- linkage: The method used to calculate distances between clusters in hierarchical clustering (e.g., 'ward'). Different methods produce different cluster shapes.