How would you handle an imbalanced dataset?
- 1 Answers
- 334 Views
- I also Faced
- E-Mail Answers
Answer / Amit Rawat
To manage an imbalanced dataset, techniques like SMOTE (Synthetic Minority Over-sampling Technique) and SMOTE-ENN can be used for over-sampling the minority class. Under-sampling the majority class or applying cost-sensitive learning, class weighting, and ensemble methods are other strategies to address this issue.
| Is This Answer Correct ? | 0 Yes | 0 No |
What is an Incremental Learning algorithm in the ensemble?
What is naive bayes classifier?
What happens if the components are not rotated in PCA?
What is svm in machine learning? What are the classification methods that svm can handle?
Explain me what is bayes' theorem? How is it useful in a machine learning context?
What is encoder and decoder in machine learning?
Is octave good for machine learning?
Why do we need to convert categorical variables into factor? Which functions are used to perform the conversion?
What is ‘tuning’ in ML?
What are the different types of algorithm methods in machine learning?
Why is Python better for machine learning?
What is boosting in Machine Learning?
-
AI Algorithms (74) - AI Natural Language Processing (96)
- AI Knowledge Representation Reasoning (12)
- AI Robotics (183)
- AI Computer Vision (13)
- AI Neural Networks (66)
- AI Fuzzy Logic (31)
- AI Games (8)
- AI Languages (141)
- AI Tools (11)
- AI Machine Learning (659)
- Data Science (671)
- Data Mining (120)
- AI Deep Learning (111)
- Generative AI (153)
- AI Frameworks Libraries (197)
- AI Ethics Safety (100)
- AI Applications (427)
- AI General (197)
- AI AllOther (6)
