Overfitting a dataset - Study guides, Class notes & Summaries

_____________ of data is used to assess the performance of each supervised learning model so that we can compare models and pick the best one. - The test partition - The validation partition - ️️Validation The validation partition is used to assess the performance of each supervised learning model so that we can compare models and pick the best one. In some algorithms (e.g., classification and regression trees, k-nearest neighbors) the validation partition may be used in automated fas...

What is Machine Learning? Machine learning is a branch of computer science which deals with system programming in order to automatically learn and improve with experience. For example: Robots are programed so that they can perform the task based on data they gather from sensors. It automatically learns programs from data. Mention the difference between Data Mining and Machine learning? Machine learning relates with the study, design and development of the algorithms that give computers ...

LIFSCI 7B XL - Working with Data Questions and Answers Graded A+ What is the first step when analyzing a new dataset? The initial step is to explore and clean the data, ensuring accuracy by identifying and handling missing or incorrect values. How does data normalization improve the quality of analysis? It scales different data features to a common range, making comparisons more meaningful and reducing the impact of extreme values. Why is it important to understand the distributi...

According to the documentation, a silhouette score of -1 is - The worst score According to the documentation, a silhouette scores of 1 ia - The best score All the the nodes prior to the output nodes essentially 'guess' at the correct weights. Then the algorithm checks to see if the initial guess is correct (usually not). When it is wrong... - It tries again (runs another epoch) An example this week was done in a Jupiter like environment called Google Collab. What was the language that wa...

According to the documentation, a silhouette scores of 1 is _____, and -1 is _____. - the best score; the worst score All the nodes prior to the output nodes essentially 'guess' at the correct weights. The algorithm checks to see if the initial guess is correct (usually not). When it is wrong... - ... it tries again (runs another epoch) An example this week was done in Jupiter like environment called Google Collab. What was the language that was demonstrated in the videos? - TensorFlow ...

What is PCA? (5 key points) Principal Component Analysis is a statistical technique used for dimensionality reduction, crucial when dealing with high-dimensional data in machine learning. It works by transforming original variables into new ones, called principal components, which are linear combinations of the original variables. Key Points: 1. Principal Components: Principal components are the directions in the data that maximize variance. The first principal component captures the most...

Identify whether the task required is supervised or unsupervised learning: Deciding whether to issue a loan to an applicant based on demographic and financial data (with reference to a database of similar data on prior customers). - Supervised - Unsupervised -:- Supervised This is supervised learning, because the database includes whether the loan was approved or not. Identify whether the task required is supervised or unsupervised learning: Printing of custom discount coupons at t...

BA 304 Midterm Exam | Questions with Verified Answers Which of the following is the correct definition of algorithms? mathematical formulas placed in software that performs an analysis on a dataset Select all of the following that represent forms of structured data. (Check all that apply.) - sensor data - web log data - clickstream data - point-of-sale data Select the four common characteristics of big data along with the correct definition. (Check all that apply.) - variety—represents diffe...

What is the purpose of a loss function in a neural network? a) To increase the model's accuracy b) To measure the performance of the model c) To calculate the number of layers in the network d) To initialize the weights of the network - correct answer b) To measure the performance of the model Which of the following is a method to prevent overfitting in a neural network? a) Dropout b) Increasing the number of layers c) Using a larger dataset d) Increasing the learning rate - correct answer a...

5 steps to building a machine learning model - 1. choosing a class of model 2. choose hyperparameters 3. arrange data 4. fit the model 5. predict a silhouette score of 1 is the [best/worst] and -1 is the [best/worst] score - best, worst basic idea of regression - we have some X values called features and some Y value, the variable we are trying to predict Difference between unsupervised and supervised learning - unsupervised: you have an X but no Y supervised: you have an X and a Y Ima...