What is the meaning of overfitting in machine learning?
Answer / Pradeep Kumar Mishra
Overfitting in machine learning refers to a situation where a model learns the training data too well, including its noise and outliers, to the extent that it negatively impacts the model's ability to generalize and make accurate predictions on unseen data.
| Is This Answer Correct ? | 0 Yes | 0 No |
What do you understand by Eigenvectors and Eigenvalues?
How do you ensure you're not overfitting with a model?
How will you choose the most appropriate machine learning algorithm for your classification problem?
What is symbolic learning in AI?
Define A HashTable in Machine Learning?
Is regression a machine learning?
What is ‘tuning’ in ML?
Tell me how a roc curve works?
Explain how do you handle missing or corrupted data in a dataset?
Which language is better for machine learning?
What is batch size machine learning?
Can naive bayes be used for multiclass classification?
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)