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BegalBoi t1_ix40w8x wrote

How can I balance an independant variable for K-Nearest Neighbour model (or any regression model).
So I have dataset for electricity consumption of a city for a year which consists of 7 independant variables out of which the windspeed column has values ranging from 3 to 570 (units). I am getting an accuracy of only 3%, no matter which model I use.
Can anyone suggest how would I balance my dataset to predict electrcity consumption.

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I-am_Sleepy t1_ix8etfd wrote

  • Have you scaled your data? If one signal magnitude too large, it can dominate the others, if not try StandardScaler, or PCA Decomposition
  • Why use kNN? Why not other models? But if you are somewhat lazy, there is Pycaret you can try (It automagically preprocess data + compare a lot of models for you)
  • Also is it a time-series data?
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