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[Show more]Descriptive Question - Questions that ask for explanations of what happened 
Predictive Questions - Questions that ask what's going to happen in the future 
Prescriptive Questions - Questions that ask what action or actions would be best 
General Questions - Generic questions on data analytics 
Mod...
Preview 1 out of 3 pages
Add to cartDescriptive Question - Questions that ask for explanations of what happened 
Predictive Questions - Questions that ask what's going to happen in the future 
Prescriptive Questions - Questions that ask what action or actions would be best 
General Questions - Generic questions on data analytics 
Mod...
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 
...
Preview 2 out of 10 pages
Add to cartSupport 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 
...
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 classificat...
Preview 2 out of 14 pages
Add to cartRows - 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 classificat...
1-norm - Similar to rectilinear distance; measures the straight-line length of a vector from the 
origin. If z=(z1,z2,...,zm) is a vector in an m-dimensional space, then it's 1-norm is square 
root(|
Preview 4 out of 32 pages
Add to cart1-norm - Similar to rectilinear distance; measures the straight-line length of a vector from the 
origin. If z=(z1,z2,...,zm) is a vector in an m-dimensional space, then it's 1-norm is square 
root(|
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