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


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.

| improve this answer | |

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.