you will learn how to manually classify and cluster data based on a specific variable using R programming language. consists of retrieving data, classifying, plot a graph and interpretation of the outcomes. The dataset that are going to be used in this project is “mtcar” that is available in R studio. Methodology: Using the number of cylinders (cyl column) in mtcar dataset(below), classify cars as 4-, 6- or 8-cylinders car. For each class, give a color to the values that belong to that class. Then plot a graph for using “mpg” column as x-axis and “qsec” column as y-axis.   Steps: Read the file using R programming language. Read values in column “cyl”. If x =8, then paint as red, if x =6, then paint as green, If x =4, then paint as blue. Plot the values of the columns mpg and qsec into an x&y graph. Plot painted values of “cyl” on the same graph. Finally, you have to add your interpretations of the results. This is very important!

TODO: Lienar Regression with least Mean Squares (LMS) Optimize the model through gradient descent. *Please complete the TODOs. * !pip install wget import osimport randomimport tracebackfrom pdb import set_traceimport sysimport numpy as npfrom abc import ABC, abstractmethodimport traceback from util.timer import Timerfrom util.data import split_data, feature_label_split, Standardizationfrom util.metrics import msefrom datasets.HousingDataset import HousingDataset class BaseModel(ABC):    """ Super class for ITCS Machine Learning Class"""     @abstractmethod    def fit(self, X, y):        pass     @abstractmethod    def predict(self, X):        pass class LinearModel(BaseModel):    """        Abstract class for a linear model         Attributes        ==========        w       ndarray                weight vector/matrix    """     def __init__(self):        """            weight vector w is initialized as None        """        self.w = None     # check if the matrix is 2-dimensional. if…

To begin with, why is it necessary to divide the data into training and validation sets? What is the training set going to be utilized for? The function of the validation set is still a mystery.

This question tests your understanding of data transformation.  We did an assignment on this process.  If you test your data and find that it is not suitable for testing, which mathematical function can you put each score through to make it usable and suitable for testing? Select one: a. There is no way to make the data usable. b. square root each number c. subtract the df from each number d. use the variance instead of each number Clear my choice