Google Trends
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Avoiding Misleading Data in Google Trends for ML
Read Full Article: Avoiding Misleading Data in Google Trends for ML
Google Trends data can be misleading when used in time series or machine learning projects due to its normalization process, which sets the maximum value to 100 for each query window independently. This means that the meaning of the value 100 changes with every date range, leading to potential inaccuracies when sliding windows or stitching data together without proper adjustments. A robust method is needed to create a comparable daily series, as naive approaches may result in models trained on non-comparable numbers. By understanding the normalization behavior and employing a more careful approach, it's possible to achieve a more accurate analysis of Trends data, which is crucial for reliable machine learning outcomes.
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