K means clustering - Samenvattingen, Aantekeningen en Examens

Support Vector Machine - A supervised learning, classification model. Uses extremes, or identified points in the data from which margin vectors are placed against. The hyperplane between these vectors is the classifier SVM Pros/Cons - Pros: It works really well with a clear margin of separation It is effective in high dimensional spaces. It is effective in cases where the number of dimensions is greater than the number of samples. It uses a subset of training points in the decision functio...

Classification problems are commonly solved using what model(s)? Support Vector Machine Clustering problems are commonly solved using what model(s)? k-means Response Prediction questions are commonly solved using what model(s)? -ARIMA -CART -Exponential smoothing -linear regression -logistic regression -Random Forest Validation questions are commonly solved using what model(s)? -Cross Validation Variance Estimation questions are commonly solved using what model(s)? -GARCH Exampl...

ISYE-6501 Exam 1 QUESTIONS & CORRECT ANSWERS Algorithm - ANSWER a step-by-step procedure designed to carry out a task Change Detection - ANSWER Identifying when a significant change has taken place Classification - ANSWER Separation of data into two or more categories Classifier - ANSWER A boundary that separates data into two or more categories Cluster - ANSWER A group of points that are identified as being similar or near each other Cluster Center - ANSWER In some clustering ...

Rows Data points are values in data tables Columns The 'answer' for each data point (response/outcome) Structured Data Quantitative, Categorical, Binary, Unrelated, Time Series Unstructured Data Text Support Vector Model Supervised machine learning algorithm used for both classification and regression challenges. Mostly used in classification problems by plotting each data item as a point in n-dimensional space (n is the number of features you have) with ...

UGBA 104 Midterm Exam Questions and Answers 100% Verified calculate outliers IQR method - CORRECT ANSWER-IQR below; Q1 - 1.5 * IQR IQR above; Q3 + 1.5 * IQR how to calculate percentiles - CORRECT ANSWER-percentile (L) = (n+1) * P/100 calculate z score outlier - CORRECT ANSWER-(value-mean)/SD rule of thumb for z score outlier - CORRECT ANSWER-above or below 3 SDs away which outlier method is more lenient - CORRECT ANSWER-z score, it goes further from mean than the IQR method ie the IQR...

ISYE 6501 - Introduction to Analytics Weeks 1 – 7 Combined Frequent Exam Questions Correctly Answered Support Vector Machine (SVM) - ANSWER Supervised learning classification tool and algorithm that seeks a dividing hyperplane for any number of dimensions can be used for regression or classification. Margin of Error (SVM) - ANSWER A small margin for error reduces your chances of misclassifying known data points but increases your chances of misclassifying unknown data points. ...

QMB3302 Final UF Verified A+ The correct number of clusters in Hierarchical clustering can be determined precisely using approaches such as silhouette scores (True or False) ️️False In K Means clustering, the analyst does not need to determine the number of clusters (K), these are always derived analytically using the kmeans algorithm. (True or False) ️️False One big difference between the unsupervised approaches in this module, and the supervised approaches in prior modules:...

What do descriptive questions ask? What happened? (e.g., which customers are most alike) What do predictive questions ask? What will happen? (e.g., what will Google's stock price be?) Brainpower Read More 0:05 / 0:15 What do prescriptive questions ask? What action(s) would be best? (e.g., where to put traffic lights) What is a model? Real-life situation expressed as math. What do classifiers help you do? differentiate What is a soft classifier and when is it...

ISYE 6501 - Introduction to Analytics Weeks 1 – 7 Combined Frequent Exam Questions Correctly Answered Support Vector Machine (SVM) - ANSWER Supervised learning classification tool and algorithm that seeks a dividing hyperplane for any number of dimensions can be used for regression or classification. Margin of Error (SVM) - ANSWER A small margin for error reduces your chances of misclassifying known data points but increases your chances of misclassifying unknown data points. ...

ISYE-6501 Exam 1 Top Questions and answers, 100% Accurate. Rated A+ Algorithm - -a step-by-step procedure designed to carry out a task Change Detection - -Identifying when a significant change has taken place Classification - -Separation of data into two or more categories Classifier - -A boundary that separates data into two or more categories Cluster - -A group of points that are identified as being similar or near each other Cluster Center - -In some clustering algorithms ...