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Can I use KNN WG for prediction short term (3 day) weather forecasting?

KNN WG is a tool for weather data generation. KNN WG is based on k-NN method. The k-NN method can generate weather data from tomorrow until a long time, but it has lots of uncertainty. It's better, you use NWP models for nowcasting weather prediction or use the famous websites such as: AccuaWeather.com, Weather.com, or etc..

The k-NN technique is based on selecting a specified number of days similar in characteristics to the day of interest from the historical record. In another word, k-NN has a resampling strategy for generating data on the basis of "similarity" from the historical period of weather data.

The k-NN technique is based on selecting a specified number of days similar in characteristics to the day of interest from the historical record. In another word, k-NN has a resampling strategy for generating data on the basis of "similarity" from the historical period of weather data. The K-nearest neighbors (k-NN) is an analogous approach. This method has its origin as a non-parametric statistical pattern recognition procedure to distinguish between different patterns according to a selection criterion. Through this method, researchers can generate future data. In other words, the k-NN is a technique that conditionally resamples the values from the observed record based on the conditional relationship specified. The k-NN is a most simple approach. The most promising non-parametric technique for generating weather data is the k-nearest neighbor (k-NN) resampling approach. The k-NN method is based on recognizing a similar pattern of target file within the historical observed weather data which could be used as a reduction of the target year.

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