Machine learning: What is the best feature selection method for binary data? And why?

Machine learning: What is the best feature selection method for binary data? And why?
What does it means to get the same feature selected for all
classifier in machine learning? Give a reaseach base answer of
atleast 500 words. Also look at the table 5 below for more
understanding of my question.
In the filter methods, the results showed that all tested classifiers left with same top ten features in the same order. (Table 5). This could indicate what? Table 5. List of the ranked features by filter method ML Classifiers Global minimum of...
What is your best way of learning and give reasons why it is the best way for you to learn.
Implement the following machine learning tasks, utilizing Regression techniques e Prediction e Classification eFeature Reduction Feature Independence Model Selection (underfitting and overfitting analysis) 2 Required Components You may utilize Python or Matlab libraries, for the following implementations. 1. Implement prediction utilizing multiple linear regression on a data set with several features Perform an evaluation of the residuals to check for assumptions of your model, such as li earity, noise term with zero mean and constant variance, normality and so forth....
AI, Robotics, Machine Learning, etc. 1. How do we distinguish between robotics and machine learning? 2. What are some ways in which Machine Learning (ML) is being used in business? 3. What is the need for ‘training data?’ Exactly who or what is being trained? 4. What are the two kinds of ‘learning’ that we talk about in ML? a. What is the difference between the two? b. Why is it significant?
Explain what is meant when people refer to ‘the Deep Learning’ revolution in Machine Learning and Artificial Intelligence. Do you think it is just ‘Hype’ (unjustified or exaggerated ‘grandstanding’), or do you feel there is something significant happening with it? Justify your answer using terms such as ‘feature map’ and ‘supervised’ and ‘unsupervised learning’. How do people overcome challenges of the scale of the numerical optimization and the large-parameter-related generalization issues which arise?
What is different in letting machine learning algorithms to learn about numeric data versus categorical data?
What method, direct or indirect, would be best for studying animals that migrate and why? What types of data might this include?
This is Intro to Deep Learning Why CNN (Convolutional Neural Network) are best tool for solving visual classification problems? Describe data augmentation process for reducing overfitting.
Question: Discuss roles of Artificial Intelligence and Machine Learning in Big Data Analytics. Distinguish between Supervised and Unsupervised learning. Discussion Requirements: Define the concept of Artificial Intelligence. Define the concept of Machine Learning. Explain the notions of Supervised and Unsupervised Machine Learning. Describe the roles of Artificial Intelligence & Machine Learning in Big Data Analytics.