What is the primary focus of regression analysis in statistics? Calculating the mean of a dataset Finding the relationship between two variables X and Y Identifying the median of a dataset Determining the mode of a dataset

Finding the relationship between two variables X and Y

In regression analysis, what is the difference between Y and Y-hat? Y is the target vector, and Y-hat is the model's prediction Y is the input variable, and Y-hat is the output variable Y is the model's prediction, and Y-hat is the target vector Y is the independent variable, and Y-hat is the dependent variable

Y is the target vector, and Y-hat is the model's prediction

What is the significance of the word 'model' in the code 'model = LinearRegression(fit_intercept=True)'? It is a command to execute the regression It is a placeholder for data input It is a keyword in Python for defining functions It is a named variable holding the linear regression model

It is a named variable holding the linear regression model

What is a good model fit value in regression analysis? Always 0.95 or higher Always exactly 1.0 Unknowable without understanding the context and domain Always 0.5 or lower

Unknowable without understanding the context and domain

Which of the following are problems with the holdout method for validation? Outliers can skew results; model not trained on all data Model is trained on all data; no outliers affect results Data is always perfectly split; results are always accurate Validation is unnecessary; results are always reliable

Outliers can skew results; model not trained on all data

What is holdout validation in the context of machine learning? Separating data into training and testing sets for validation Ignoring validation to focus on model accuracy Using all data for training without testing Testing the model on the same data used for training

Separating data into training and testing sets for validation

What is a random forest in machine learning? A linear regression model with multiple variables A clustering algorithm for unsupervised learning A single decision tree used for predictions A collection of decision trees aggregated into one result

A collection of decision trees aggregated into one result

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Cards in this deck(46)

What is the primary focus of regression analysis in statistics?

In regression, X values are called _____, and Y values are what we are trying to _____.

In regression analysis, what is the difference between Y and Y-hat?

What is the significance of the word 'model' in the code 'model = LinearRegression(fit_intercept=True)'?

What is a good model fit value in regression analysis?

Which of the following are problems with the holdout method for validation?

What is holdout validation in the context of machine learning?

In a decision tree, what is the first variable called before any branches?

One problem with a decision tree is that you are prone to _____ if you do not set the _____ appropriately.

What is a random forest in machine learning?

Does the random forest algorithm help prevent overfitting found in decision trees?

Can random forests be used for both regression and classification tasks?

Is it necessary to run a linear regression to interpret decision trees?

Are decision trees simple and straightforward to interpret?

What happens when 'maxdepth=' is removed in a decision tree?

What is the terminal node in a decision tree?

What is Scikit-learn in the context of machine learning?

What is the best source for up-to-date information on parameters for models like random forest?

Random forests are _____ interpretable than decision trees.

What is hierarchical clustering in unsupervised learning?

Can the correct number of clusters in hierarchical clustering be determined precisely?

What is K-means clustering?

In K-means clustering, does the analyst need to determine the number of clusters (K)?

Do unsupervised models have a target variable (Y)?

According to the documentation, a silhouette score of 1 is the _____ and a score of -1 is the _____.

What approaches could you use to understand more about customers with given data columns?

What is the purpose of the code using 'StandardScaler' from sklearn?

What is the elbow method in the context of K-means clustering?

Does the elbow method provide an exact number of clusters for a K-means algorithm?

Is hierarchical clustering more powerful than K-means for determining the exact number of clusters?

In K-means, the algorithm begins by assigning the first centroids to _____ and then _____ of each point to the centroid.

What does NLP stand for in the context of machine learning?

What is tokenization as defined in natural language processing?

What are recommender systems in the context of machine learning?

What are two common types of recommenders discussed in the lecture?

Which model approaches could work when building a model with continuous predictor and target variables?

What is a common problem associated with decision trees?

In linear regression, A is commonly known as the _____ and B is commonly known as the _____.

Is the Linear Regression estimator only capable of simple straight line fits?

What are the 5 steps to building a machine learning model as discussed in class?

What is the purpose of the code 'import matplotlib.pyplot as plt; import seaborn as sns; import numpy as np'?

What is the primary use of Matplotlib in data analysis?

What characterizes an unsupervised model in machine learning?

What characterizes a supervised model in machine learning?

What kind of model are you building if you have a bunch of X's but no Y's?

What is one reason linear regression is a good starting point in modeling tasks?

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QMB Final Exam

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