I have a ML model made with "knn" in scikit-learn and noticed that the more i have data, more precise my model is getting with it's predictions. The problem is, i have lot's of DataFrames that show different situations for the same system i want to predict. Is it possible to train the model in those different Dataframes? Because if i call .fit() it'll reset it's previous trainning. X_cleaned = X.dropna() y_cleaned = y[X_cleaned.index] X_training, X_test, y_training, y_test = train_test_split(X_cleaned, y_cleaned, test_size=0.15, random_state=0) Continue reading...
