Imagine that you have access to a database with the names and x, y locations of many different places. Let's say that only the following kinds of questions are being asked: The main question of the study is whether or not there is a restaurant at a certain location. Which way of sorting is better: Is it a B-tree or an R-tree? Why?

Use examples to justify your machine learning model choice. Two novel ways to categorise things include the K-nearest neighbour, looking backward, and gathering supplementary information.

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Four different machine learning algorithms are shown in this section, which may be used for supervised learning on a given dataset. Give a description of any four variables you may use to help you choose which one to utilize to determine whether or not a tumor is malignant.

Write short notes on: Lasso Regression

Question: Implement a simple decision tree classifier from scratch using Python. Your implementation should include functions for building the tree, making predictions, and evaluating the model using accuracy as the performance metric. Use the ID3 algorithm for building the decision tree, and handle both categorical and numerical features.

Four different machine learning algorithms are shown in this section, which may be used for supervised learning on a given dataset. Give a description of any four variables you may use to help you choose which one to utilize to determine whether or not a tumor is malignant.

In order to solve the issue of the Minimum Spanning Tree, what is the most effective approach to use Prim's method?... Do any of the other data structures have an advantage over the others? Why? Explain.

Using the same graph from the previous questions: A G C B D F E

Imagine a database that is structured like a tree with its roots at the top. Imagine for a moment that we decided to add a fake vertex in between each pair of existing vertices. Demonstrate that adhering to the tree protocol on the new tree yields superior concurrent results to adhering to the tree protocol on the initial tree.