How does factor analysis contribute to the prediction of water quality parameters algorithm Machin learning?
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Factor analysis contributes to the prediction of water quality parameters in machine learning algorithms by identifying the key factors that affect water quality . By analyzing the relationship between different parameters such as pH value, turbidity, hardness, conductivity, and dissolved solids, factor analysis helps in understanding the underlying factors that contribute to water quality . This information can then be used to develop predictive models that can classify water samples as safe or unsafe for various purposes, including drinking . Machine learning algorithms, such as decision tree regression, linear regression, and artificial neural networks, can be applied to these factors to predict water quality index and assess the effectiveness of water restoration measures . By incorporating factor analysis into the prediction process, machine learning algorithms can provide accurate and proactive measures to prevent water pollution and ensure the availability of clean water for human use .
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