Question 17If you have a dataset with small number of examples and very high number of features, in your ML, is the best choice to use gradient descent or normal equation? Why?
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Question 17
If you have a dataset with small number of examples and very high number of features, in your ML, is the best choice to use gradient descent or normal equation? Why?
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- You have four various machine learning algorithms to pick from for supervised learning on a dataset. Describe any four factors you would use to help you decide which one to employ for a certain task.You have four various machine learning algorithms to pick from for supervised learning on a dataset. Describe any four factors you would use to help you decide which one to employ for a certain task.Explain why the spiral model is better to the waterfall approach in the context of this discussion. Explain spiral model evolution.
- You have four various machine learning algorithms to pick from for supervised learning on a dataset. Describe any four factors you would use to help you decide which one to employ for a certain task.Alert dont submit AI generated answer.What is true about a validation set? its data should be similar to that of the training set we train our models on the validation set to show that they are valid the validation set is often smaller than the training set validation sets, while popular, are not necessary to produce ML models to be used in the world the validation set is the collection of y-values to the inputs to your model, which are the x-values
- Vector space classification methods frequently fail when applied to problem sets with nominal feature sets alone. What do you think of the statement? Using ML, how would you classify nominal data? Answer each of the above queries in detail.In VES modelling, what is the difference between a smooth model and a stacked model?The output for linear regression analysis has multiple numbers. How can we interpret the output? Can you share some hints.
- When the issue set contains only nominal characteristics, vector space-based classification algorithms are usually not the best solution. What are your thoughts on this statement? How would you utilise machine learning to categorise nominal data?explain the value of a data model in the context of a standard strength prediction.The benefits of switching to all-subsets regression from stepwise regression are broken forth in great depth below. .