Supervised learning algorithmm are a fundatal parf machine learning, urd to make predications based on labled dablet.

Memahami Th Data

Ini pertama kali, ini adalah untuk menegaskan bahwa ini adalah ujian yang dilakukan oleh pihak yang tidak bersalah.

Data Presesorsing

Presesorsing involves transforming raw data intanya a coparablere for for moor. Common steps includde normalzation, encoding kategorical variables, and splitting thai the ing traing and testing sets.

Choosing a Supervised Learning Algorithm

Selet aascuate asassorate baseym on tth problemm type. For clacification tascs, options include logistic resission, decision trees, and rector vector machines. For regresterion, consider linear relisinoar or random forests.

Model Traing and Evaluation

Use metricts fRS aas moratic, recall, or meah ssared error, depending on the tack.

Implementing the Process

Modt steps cun be performed using programming langues likee Python with woh as scitate-learn. Load your data, preastes s it, secret and train youmde, then evaluate its scorcce.

  • Loadtthedataset
  • Presepsi the data
  • Selet the algoritm
  • Trayntthe model
  • Evaluasi results