Interested to Buy Any Domain ? << Click Here >> for more details...
Describe dimension reduction in machine learning.
- 1 Answers
- 95 Views
- I also Faced
- E-Mail Answers
Answer / Arpit Gautam
Dimension Reduction is the process of transforming a high-dimensional dataset into a lower-dimensional space while retaining most of the original information. This helps to reduce overfitting, improve computation efficiency, and visualize complex data. Techniques for dimensionality reduction include Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Non-negative Matrix Factorization (NMF), and t-SNE.
| Is This Answer Correct ? | 0 Yes | 0 No |
How do you control for biases?
Explain the Algorithm of Nearest Neighbor in Machine Learning?
What is batch in machine learning?
What is Perceptron in Machine Learning?
How to choose notable variables while working on a data set?
What are the recommended systems?
What is data augmentation? Can you give some examples?
Explain the 3 types of ai?
What is Genetic Programming?
What are the three types of algorithms?
What is ROC curve and what does it represent?
What is ensemble 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)
