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I was trying to build a CNN model. I used time series data of daily temperature to predict if there is risk of an event, say bacteria growth. I calculated the descriptive statistics of the time series, ie. mean, variance, skewness, kurtosis etc for each observation and added them to input data.

My question:

Is CNN capable of extracting the effect of the descriptive statistics the label, meaning that adding these descriptive statistics features manually does not make a difference? (I will still try this later, but like to hear what you think about it). Thanks

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That is definitely not what CNNs are designed for. CNNs learn convolutional filters that get trained on finding local, recurring patterns in some kind of image/volume data. 1D convolution is actually a thing, but I think what would be more suitable for your case is using Recurrent Neural Nets. They are specifically designed for working on time series-es of heterogeneous data.

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