April 2019
Intermediate to advanced
426 pages
11h 13m
English
Content preview from Mastering Python for Finance - Second Edition
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K-means clustering
The k-means clustering algorithm is a method of clustering analysis in data mining. From the backtest results of n observations, the k-means algorithm is designed to classify the data into k clusters based on their relative distance from one another. The center point of each cluster is computed. The objective then is to find the within-cluster sum of squares that gives us a model-averaged point. The model-averaged point indicates the likely average performance of the model, which can be used for further comparison with the performance of other models.
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