Interested to Buy Any Domain ? << Click Here >> for more details...
Tell us what evaluation approaches would you work to gauge the effectiveness of a machine learning model?
- 1 Answers
- 85 Views
- I also Faced
- E-Mail Answers
Answer / Km Gargi
The evaluation approaches for gauging the effectiveness of a machine learning model include but are not limited to: Cross-validation, K-Fold Cross-Validation, Leave-One-Out Cross-Validation, Train-Test Split, and Bootstrapping. These methods help in determining the model's generalization performance on unseen data by splitting the available data into training and testing sets.
| Is This Answer Correct ? | 0 Yes | 0 No |
What is the “curse of dimensionality?
What is 'naive' in the Naive Bayes classifier?
What is svm in machine learning? What are the classification methods that svm can handle?
When should you use classification over regression?
“People who bought this, also bought….” Recommendations on amazon are a result of which machine learning algorithm?
What is dimensionality reduction? Explain in detail.
How do you ensure you're not overfitting with a model?
What is Genetic Programming?
Which is the best language for machine learning?
Explain me what cross-validation technique would you use on a time series dataset?
What are the three stages of building the hypotheses or model in machine learning?
How was bayes’ theorem useful in a machine learning context?
-
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)
