Observed signal Missing Data et's say you're given a signal with some missing data, as shown in the figure above, and your oal is to fill in the blanks. 1. Would you say that this is a supervised learning, or an unsupervised learning problem? 2. Which of the following models do you think fits the data above? o y = A cos(wt + 4) o y = Aj cos(wit + o1) + A2 cos(wat + 2) o y = Ae-kt cos(wt + 4) 3. Describe how you would proceed to solve it if you were given such a problem.

The question of the course called Information Theory and Learning is explained in the visual, can you please do the solution in an explanatory and simple way?

Program important

Subject: Machine Learning Question Number 5 : What are Ensemble Algorithms? Write an algorithm for BOOSTING method. Assume that two individuals offer to sell you their predictive models M1 and M2. The confusion matrices produced by each model are as follows. What is the accuracy of each model? Assuming that precision is of paramount importance in your application, which of the two models would you buy? Why?

Discuss lazy learning using the KNN algorithm When shall we use/not use kNN for classification?

Short questions. Please choose the right choices for each question. There may be more than one correct choice. 1. A machine learning model usually has a few hyper-parameters to tune. Which of the two following settings are good for choosing hyper-parameters that can generalize well to new data: (a) Choose hyperparameters that work best on the all data (b) Choose hyperparameters that work best on the training set (c) Choose hyperparameters that work best on the validation set (d) Choose hyperparameters by performing k-fold cross-validation.

Question Sum   Full explain this question and text typing work only      We should answer our question within 2 hours takes more time then we will reduce Rating Dont ignore this line

Consider the following points. Below are some graph-like structures, along with examples of how they've been used in AI models.a. The term "K-means"b. Closest neighbours (K)c. Decision tressConsider the following points. Below are some graph-like structures, along with examples of how they've been used in AI models.a. The term "K-means"b. Closest neighbours (K)c. Decision tress

Should I always treat outliers before building my machine learning model or just leave the outlier in my data