Question

You have built a classification model with 90% accuracy but your client is not happy, because false positive rate was very high then what will you do?

Answer 1

Answer:

Explanation:

1) Missing value analysis and imputation

2) Feature engineering

3) Normalisation and standardisation

4) Cross validation measures

5) Fine-tuning hyper parameters boosting Algorithms

6) Ensambling

7) Collecting more data

8) Synthesizing more data

You should try these measures and evaluate if performance increases