K means clustering - Study guides, Class notes & Summaries

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...

Data point - Observation/record of (perhaps multiple) measurements for a single member of a population or data set. In the standard tabular format, a row of data. Bayesian Information criterion (BIC) - Model selection technique that trades off model fit and model complexity. When comparing models, the model with lower BIC is preferred. Generally penalizes complexity more than AIC. 1-norm (rectilinear distance, Manhattan distance) - Think of distances in blocks E (|xi - yi|) 2-norm (euclide...

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 ...

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 ...

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 - 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. ...

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...

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...

Data Science - ANSWER interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured 3 Analytical Approaches to Predictive Analytics - ANSWER Statistics, Artificial Intelligence, Machine Learning Statistics - ANSWER the foundation for predictive analytics -- the building blocks Ex: regression, factor & cluster analysis Artificial Intelligence - ANSWER uses heuristics- "rules of t...

What do descriptive questions ask? - CORRECT ANSWER-What happened? (e.g., which customers are most alike) What do predictive questions ask? - CORRECT ANSWER-What will happen? (e.g., what will Google's stock price be?) What do prescriptive questions ask? - CORRECT ANSWER-What action(s) would be best? (e.g., where to put traffic lights) What is a model? - CORRECT ANSWER-Real-life situation expressed as math. What do classifiers help you do? - CORRECT ANSWER-differentiate What is a soft...