Introduction to Machine Learning
Showing 76-150 of 163 answers
Overfitting happens when the model does not adequately fit the facts
- True
- False Correct
Overfitting indicates that your model makes a valiant effort to precisely fit all the data
- True Correct
- False
Pie charts can have labels added to them, but first, you must deal with the values returned by the pie() function
- True
- False Correct
Rather than having to retrain the model each time you have new data to test, a stored model allows you to load the trained model and make predictions without having to retrain the model
- True Correct
- False
Running a code outside Jupyter Notebook would have a significantly better way of presenting the 3D plot
- True Correct
- False
Set the inplace argument to True if you want the original DataFrame to be sorted
- True Correct
- False
Setting the x-axis to start at 45 and expanding the range of the y-axis is a better visualization approach 0
- True
- False Correct
Since you are familiar with the intercept and coefficients of the polynomial multiple regression function, you can quickly visualize the 3D prediction function
- True
- False Correct
Slicing is also applicable to both Series and DataFrames in Pandas
- True Correct
- False
Starting with linear regression is the simplest method to get started with machine learning with Scikit-learn
- True Correct
- False
Sub plots can also be plotted separately and then combined into a single figure Multiple scatter plot
- True
- False Correct
SVM uses the kernel trick to deal with datasets that are not linearly separable
- True Correct
- False
Swarmplots are identical to line graphs that show how much one variable is affected by the presence of another, and this relationship between two variables is statistically termed as their correlation Scatter plots
- True
- False Correct
The =E2=80=98as np' portion of the code tells Python to bring the NumPy library into your current environment
- True
- False Correct
The basic notion behind polynomial regression is finding the polynomial function's prediction that best matches the data
- True
- False Correct
The best hyperplane is that plane with the shortest distance from both classes, which is SVM's main aim
- True
- False Correct
The best k is chosen for each k, which reveals the k with the lowest MSE MSE
- True
- False Correct
The concentric rings drawn around the test point are based on the values of k, which range from 7 to 1, with intervals of -2
- True Correct
- False
The degree of the polynomial features is specified by a number the PolynomialMultiple class accepts
- True
- False Correct
The describe indexer can also be used to extract rows based on the row number
- True
- False Correct
The describe() function can be used to obtain numbers such as count, mean, standard deviation, minimum and maximum
- True Correct
- False
The difference between Boosting and Bagging is that each learner is trained using all the data Still, the data points that previous learners misclassified are given greater weight so that following learners will pay closer attention to them during training
- True Correct
- False
The end index is the source of most misunderstandings when it comes to slicing
- True Correct
- False
The goal of SVM is to separate the points into two or more classes so that you can use it to predict the classes of future points
- True Correct
- False
The higher the value of Gamma, the more it will try to fit the training dataset exactly, resulting in oversizing
- True
- False Correct
The index property is required if you want to extract specific rows and columns from a DataFrame
- True
- False Correct
The intercept and coefficient are currently of greatest interest to us after the model has been predicted
- True
- False Correct
The lmplot is another popular plot in Seaborn
- True Correct
- False
The main idea behind SVM is to draw a line between two or more classes in the best possible manner
- True Correct
- False
The main problem with KNN is how to determine the optimal value of k to employ
- True
- False Correct
The make regression() function produces linearly distributed data wherein you can define the number of features and the standard deviation of the Gaussian noise used in an output
- True Correct
- False
The next step is to identify the best K that yields the highest average Silhouette Coefficient once you have seen how to calculate the mean Silhouette Coefficient for a dataset with K clusters
- True Correct
- False
The number of rows required for training cannot be less than the value of k More than
- True
- False Correct
The optimal k is the one with the lowest average silhouette
- True
- False Correct
The outcome of a classification problem can also be a broken value, indicating the likelihood of an observation belonging to a particular class
- True
- False Correct
The plot() function draws points without connecting lines Depending on the inputs, may or may not be plot lines Scatter() function
- True
- False Correct
The process of making a NumPy object is similar to that of making a NumPy array
- True
- False Correct
The Scikitlearn library's sklearndatasetssamples generator module can be used to create datasets with various distributions
- True Correct
- False
The sigmoid function that tries to fit the points on the chart can be plotted using =CE=B20 and x=CE=B2
- True
- False Correct
The simplest way to begin with Scikit-learn for machine learning is to start with linear regression
- True Correct
- False
The structure of a DataFrame in Pandas demonstrates that a Series is a single column in a DataFrame along with the index
- True Correct
- False
The sum-product of two vectors is computed by multiplying the relevant entries in each vector and adding the results
- True
- False Correct
The tail() function in Python displays the last five rows of the dataframe by default
- True Correct
- False
The tail() method, like the head() function, lets you select how many rows to print
- True Correct
- False
The use pandas portion of the code tells Python to bring the panda's data analysis library into your current environment
- True
- False Correct
The visual inspection makes it simple to determine the value of K for a small dataset, but it becomes more difficult for a large sample
- True Correct
- False
There are numerous classes and functions for handling polynomial regression in the StatLib
- True
- False Correct
There is another fundamental distinction between multiplications on an index array and a matrix
- True
- False Correct
To avoid occurrences when there is a tie between the classes in a two-class problem, k should have an even value Odd
- True
- False Correct
To combine two arrays, you can use the npconcat() function instead of the + operator
- True
- False Correct
To display a 3D plot in python, you need to type in the command $ python filenamepy
- True Correct
- False
To generate datasets with different distributions, use the sklearndatasetssamples generator module of the Scikitlearn package
- True Correct
- False
To illustrate how one variable influences the value of another, factor charts are widely used
- True
- False Correct
To prevent knots, similar to the preceding point, the number of classes must not be a multiple of the value of N k
- True
- False Correct
To run or execute a code in Jupyter Notebook, you need to save the code with an extension name of py and remove the first line that contains the expression "%matploblib inline"
- True Correct
- False
To train a model in Scikit-learn, you usually utilize the predict() function Fit() function
- True
- False Correct
Unlabeled data lacks a label Hence the fact that we can identify patterns in it is of interest to us because there is no label in unlabeled data
- True Correct
- False
Unsupervised learning algorithms aim to uncover associations in data that do not have labels
- True Correct
- False
Unsupervised learning's purpose is to predict a pattern in a dataset
- True Correct
- False
Use DataFrameplot to access the shape of a Pandas DataFrame; the shape property provides a tuple that indicates the dimensionality of the DataFrame DataFrameshape
- True
- False Correct
Using a linear object, you can build a new feature matrix from any polynomial combinations of features with a degree less than or equal to the desired degree
- True
- False Correct
Using a polynomial regression line is not always necessary to capture the correlations between the features and labels
- True
- False Correct
Using python commands, you can rotate and interact with the chart
- True Correct
- False
Various models are utilized in the ensemble learning technique in order to work together on a single dataset, and the results are then combined
- True Correct
- False
We can plot a linear regression using a specific code snippet after the values of =CE=B20 and x=CE=B2 are obtained
- True
- False Correct
When cells run, a running number displays the sequence in which they are executed
- True Correct
- False
When displaying percentages or proportions of data, a pie chart is beneficial
- True Correct
- False
When learning Python, it is generally helpful to begin with a simple dataset that you may construct yourself to ensure that the algorithm is performing correctly according to your understanding Machine learning algorithm
- True
- False Correct
When matplotlib loads a dataset with empty fields, it will represent those fields with NaN Pandas
- True
- False Correct
When one variable rises while the other rises or when one variable fall while the other falls, there is a positive correlation
- True Correct
- False
When performing multiplications on an index array and a matrix, there is another significant difference
- True
- False Correct
When the axis parameter is set to 0, it means you wish to sort by index
- True Correct
- False
When the bbox inches parameter is set to zero, the surplus white space surrounding your figure is removed Tight
- True
- False Correct
When the frequency is set to year, the last day of the month will be the day of each date
- True
- False Correct
When using a KNN, increasing k tends to make your prediction more resistant to data noise
- True Correct
- False
