Interested to Buy Any Domain ? << Click Here >> for more details...
Tell us what kind of problems does regularization solve?
- 1 Answers
- 93 Views
- I also Faced
- E-Mail Answers
Answer / Nandpal Tyagi
Regularization is a technique used in machine learning to prevent overfitting, where a model becomes too complex and performs poorly on unseen data. It works by adding a penalty term to the cost function (loss function) that encourages simpler models by penalizing large coefficients or weights. Common regularization techniques include L1 (Lasso) and L2 (Ridge) regularization, which differ in the type of penalty term applied.
| Is This Answer Correct ? | 0 Yes | 0 No |
What are the most important machine learning techniques?
How is machine learning used in day-to-day life?
Mention the difference between Data Mining and Machine learning?
Is Python enough for machine learning?
What is the bias in machine learning?
What is unsupervised learning?
What is accuracy machine learning?
Describe the relationship between machine learning and artificial intelligence?
Explain the 3 types of ai?
How is KNN different from K-means clustering?
Who is associated with the theory of symbolic learning?
How will you explain machine learning into a layperson?
-
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)
