Support vector machine - Study guides, Class notes & Summaries

ISYE 6501 REAL MIDTERM EXAM | REAL EXAM QUESTIONS WITH CORRECT ANSWERS AS PER MARKING SCHEME Instructions Work alone. Do not collaborate with or copy from anyone else. You may use any of the following resources: One sheet(both sides) of handwritten (not photocopied, scanned, or printed) notes If any question seems ambiguous, use the most reasonable interpretation (i e don't be like Calvin): Instructors know about the issue in a private Piazza post afterwards. Good luck! 1...

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

ISYE6501: MIDTERM 1 LATEST 2023 RATED A Matching models/methods to categories (cusum and pca = NONE) Select all of the following models that are designed for use with attribute/feature data (i.e., not time-series data): k-nearest-neighbor, PCA, k-means, logistic regression, linear regression, random forest, SVM's Classification models CART, k-nearest-neighbor, logistic regression, random forest, support vector machine Clustering k-means Response prediction ARIMA, Exponential smoothing, Lin...

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 2 | P a g e Variance Estimation questions are commonly solved using what model...

RowsData points are values in data tables ColumnsThe 'answer' for each data point (response/outcome) Structured DataQuantitative, Categorical, Binary, Unrelated, Time Series Unstructured DataText Support Vector ModelSupervised 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 the value of each feature being th...

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...

Support Vector Machine - CORRECT ANSWER-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 - CORRECT ANSWER-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 tra...

What does SVM stand for? : Support Vector Machine Is written text structured or unstructured? : Unstructured When we increase the sum of the square of the coefficients we... : Decrease the distance between the lines In SVM soft classifier we tradeoff between maximizing ___ and minimizing ___ : margin and errors If lambda gets small what gets emphasized, large margin or minimizing training error?, : Minimizing errors. What is a support vector? 2 | P a g e : A point that holds up a sh...

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 ...

Notes of Statistical Machine Learning containing notes on topics of linear regression, logistic regression, support vector machine, neural networks