Table 3  A comparison of the advantages and disadvantages of the three methods

Strengths

Simple, easy to understand and master

Improve extrapolation and interpretation of models

1. Applicable to datasets with diverse distribution

2. Robust to outliers and missing values

3. Allow for direct feature selection

4. Avoid over-fitting

5.Strong extrapolation capabilities

Weaknesses

1. The sensitivity to outliers

2. A weak feature selection ability

3. Overfitting

4. Limited ability to extrapolate beyond the available data

1. Filter out irrelevant features depends on prior knowledge and expertise.

2. Weak ability to handle non-linear relationships

3.May not fit accurately for complex data patterns.

Filter out irrelevant features depends on prior knowledge and expertise