Random Variables
Using Statistics for Predictive Analytics
Developing Predictive Analytics Frameworks
Data Mining Methods
Data Mining for Analyzing Sales Data
Data Mining Techniques for Service Quality
Predictive Performance
Building Predictive Models
Demand Forecasting 
Regression Analysis: Understanding the relationship between demand and various independent
variables ...Random Forest: An ensemble learning method that constructs multiple decision trees for improved accuracy
...
Using Statistics for Predictive Analytics Regression Analysis: Examines the relationship between dependent and independent
variables ...Market segmentation, risk assessment
Random Forest An ensemble method that uses multiple decision trees to improve accuracy
...
Developing Predictive Analytics Frameworks Feature Selection: Identifying the most relevant
variables that will contribute to the predictive model
...Random Forest An ensemble method that constructs multiple decision trees and merges them to improve accuracy and control overfitting
...
Data Mining Methods Association Rule Learning Finding interesting relationships (associations) between
variables in large databases
...Common algorithms used for classification include: Decision Trees Support Vector Machines (SVM) Naive Bayes
Random Forests Classification is widely used in applications such as email filtering, medical diagnosis, and credit risk assessment
...
Data Mining for Analyzing Sales Data Common algorithms used for classification include: Decision Trees
Random Forests Support Vector Machines (SVM) Naive Bayes 2
...Regression Analysis Regression analysis is employed to understand the relationship between
variables ...
Data Mining Techniques for Service Quality Random Forest An ensemble method that creates multiple decision trees and merges their results
...Association Rule Learning Association rule learning is a technique used to discover interesting relationships between
variables in large datasets
...
Predictive Performance Feature Engineering: The process of selecting and transforming
variables to improve model performance
...Customer segmentation, risk assessment
Random Forest An ensemble learning method that constructs multiple decision trees for improved accuracy
...
Building Predictive Models This process includes: Handling missing values Removing duplicates Encoding categorical
variables Normalizing or standardizing numerical features 4
...Random Forest An ensemble method that combines multiple decision trees to improve accuracy
...
Forecasting Sales with Machine Learning Models Regression A statistical method that models the relationship between a dependent variable and one or more independent
variables ...Random Forest An ensemble method that combines multiple decision trees to improve accuracy
...
Analytical Models decision trees,
random forests) 3
...They analyze data to determine why certain events occurred, providing insights into the relationships between
variables ...
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