[{"title":"( 4 个子文件 11KB ) AIR-QUALITY-PREDICTION:近年来,空气污染急剧增加,并且对所有生物造成的影响更糟。 世界上大多数国家都在与日益增加的空气污染水平作斗争。 因此,控制和预测空气质量指数已成为必要。 在此研究项目中,我们将实施数据挖掘和机器学习模型来预测AQI并将AQI归类。 对于AQI预测,我们已经实现了五个回归模型主成分,偏最小二乘法,留一维CV的主成分,留一维CV的偏最小二乘,多个印度城市的多元回归AQI数据。 根据AQI的值,AQI指数进一步分为6个不同的类别,即“好,满意,中,差,非常差和严重”","children":[{"title":"AIR-QUALITY-PREDICTION-master","children":[{"title":"Code_Files","children":[{"title":"DATASET2","children":[{"title":"K_Nearest_Neighbour_Classification_and_Multinomial_Logistic_Regression.R <span style='color:#111;'> 12.85KB </span>","children":null,"spread":false}],"spread":true},{"title":"DATASET1","children":[{"title":"PLS_PCR_regression.R <span style='color:#111;'> 11.37KB </span>","children":null,"spread":false}],"spread":true},{"title":"DATASET3","children":[{"title":"Multiple_Linear_Regression.R <span style='color:#111;'> 5.26KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"README.md <span style='color:#111;'> 1.14KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}]