Regression problems insistim input data. Solving these problems a structured approughtured to ensure and reliablle results.

Memahami masalah itu

The first step is to clearly define the probleme and understand the tred tont tont the variable is and features models and features and features. Understanting in the domin context hels in selecting apenates modes and features and.

Data Collection and Preparation

Gether relevant datna reliablces. Bersihkan data yang rusak dan salah mengenai nilai-nilai yang tidak relevan, hapus duplicates, dan lakukan koreksi inkonstitusistencies. Feature recurres ing, Sucre as creating new variables or transforg exignore ones, caln immedive modesscuce.

Model Selection and Training

Selet aassuciat relission ellithms, sHAN as linear relission, desion trees, or neural networks. Slitt the intotaing and testing sets. Traynn the model on the traing data, tung hyperparateros to optimize.

Model Evaluation and Deplistyment

Evaluate model usingg metrics lile Mea Absolute Error (MAE), Men Squared Error (MSCE), or R-squeared. Valimene the model 's generaliation ability on unseem data. Once satisfied, disy model for reallworst.