Which machine learning approach should be used to solve this problem?
Logistic regression
Random Cut Forest (RCF)
Principal component analysis (PCA)
Linear regression
Explanations:
Logistic regression is used for binary classification problems where the goal is to predict categorical outcomes, not for predicting continuous quantities like the number of units to produce.
Random Cut Forest (RCF) is primarily used for anomaly detection in streaming data, rather than for predicting continuous outcomes. It is not suitable for forecasting production quantities.
Principal component analysis (PCA) is a dimensionality reduction technique, used to reduce the number of features while preserving variance. It does not directly predict output values, making it unsuitable for this forecasting problem.
Linear regression is a statistical method used to model the relationship between a dependent variable (units to produce) and one or more independent variables (features). It is well-suited for predicting continuous quantities, making it the appropriate choice for this problem.