Analysis of the Stock Rise and Fall Prediction Model Based on the KNN Algorithm with Dynamic Parameters
Predicting stock price fluctuations is one of the important application scenarios of machine learning classification algo-rithms.According to the experience,since the data features of different stocks are not the same,the key parameter of KNN al-gorithm is adjusted when the prediction model is built.This study provides one mechanism to confirm the key parameter of KNN by the history stock data,and provides a perdition model by KNN algorithm with dynamic parameters.This model is ver-ified by different stock data,which is more accurate than any other models that all use the same parameter.
万方数据
维普
