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In this article, we will discuss the Decision Tree analysis method. 1) Classification Trees are used when the target variable is categorical and, as the name implies, are used to classify/divide the data into these predefined categories of a target variable. What is Decision Tree Analysis? Use Case – 2. About Smarten.
In this article, we will discuss the Binary Logistic Regression Classification method of analysis, and how it can be used in business. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default. What is Binary Logistic Regression Classification?
In this article, we will discuss the Binary Logistic Regression Classification method of analysis, and how it can be used in business. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default. What is Binary Logistic Regression Classification?
In this article, we will discuss the Binary Logistic Regression Classification method of analysis, and how it can be used in business. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default. What is Binary Logistic Regression Classification?
This article discusses the analytical method of Hierarchical Clustering and how it can be used within an organization for analytical purposes. Business Benefit: Once the segments are identified, the bank will have a loan applicants’ dataset with each applicant labeled as high/medium/low risk. What is Hierarchical Clustering?
This article discusses the analytical method of Hierarchical Clustering and how it can be used within an organization for analytical purposes. Business Benefit: Once the segments are identified, the bank will have a loan applicants’ dataset with each applicant labeled as high/medium/low risk. What is Hierarchical Clustering?
This article discusses the analytical method of Hierarchical Clustering and how it can be used within an organization for analytical purposes. Business Benefit: Once the segments are identified, the bank will have a loan applicants’ dataset with each applicant labeled as high/medium/low risk. What is Hierarchical Clustering?
In this article, we will discuss the KNN Classification method of analysis. The KNN (K Nearest Neighbors) algorithm analyzes all available data points and classifies this data, then classifies new cases based on these established categories. KNN Classification analysis can be useful in evaluating many types of data.
In this article, we will discuss the KNN Classification method of analysis. The KNN (K Nearest Neighbors) algorithm analyzes all available data points and classifies this data, then classifies new cases based on these established categories. KNN Classification analysis can be useful in evaluating many types of data.
In this article, we will discuss the KNN Classification method of analysis. The KNN (K Nearest Neighbors) algorithm analyzes all available data points and classifies this data, then classifies new cases based on these established categories. KNN Classification analysis can be useful in evaluating many types of data.
This article provides a brief overview of isotonic regression technique. About Smarten The Smarten approach to augmented analytics and modern business intelligence focuses on the business user and provides tools for Advanced DataDiscovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.
This article provides a brief overview of isotonic regression technique. The Smarten approach to augmented analytics and modern business intelligence focuses on the business user and provides tools for Advanced DataDiscovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.
This article provides a brief overview of isotonic regression technique. The Smarten approach to augmented analytics and modern business intelligence focuses on the business user and provides tools for Advanced DataDiscovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.
This article provides a brief explanation of the FP Growth technique of Frequent Pattern Mining. The FP Growth analytical technique finds frequent patterns, associations, or causal structures from data sets in various kinds of databases such as relational databases, transactional databases, and other forms of data repositories.
In this article, we will discuss the Decision Tree analysis method. 1) Classification Trees are used when the target variable is categorical and, as the name implies, are used to classify/divide the data into these predefined categories of a target variable. What is Decision Tree Analysis?
In this article, we will discuss the Decision Tree analysis method. 1) Classification Trees are used when the target variable is categorical and, as the name implies, are used to classify/divide the data into these predefined categories of a target variable. What is Decision Tree Analysis?
This article provides a brief explanation of the FP Growth technique of Frequent Pattern Mining. The FP Growth analytical technique finds frequent patterns, associations, or causal structures from data sets in various kinds of databases such as relational databases, transactional databases, and other forms of data repositories.
This article provides a brief explanation of the SVM Classification method of analytics. The goal is to choose a hyperplane with the greatest possible margin between the hyper-plane and any point within the training set, giving a greater chance of new data being classified correctly. What is SVM Classification Analysis?
This article provides a brief explanation of the FP Growth technique of Frequent Pattern Mining. The FP Growth analytical technique finds frequent patterns, associations, or causal structures from data sets in various kinds of databases such as relational databases, transactional databases, and other forms of data repositories.
This article provides a brief explanation of the SVM Classification method of analytics. The goal is to choose a hyperplane with the greatest possible margin between the hyper-plane and any point within the training set, giving a greater chance of new data being classified correctly. What is SVM Classification Analysis?
This article provides a brief explanation of the SVM Classification method of analytics. The goal is to choose a hyperplane with the greatest possible margin between the hyper-plane and any point within the training set, giving a greater chance of new data being classified correctly. What is SVM Classification Analysis? About Smarten.
This article provides a brief overview of random forest classification technique. The data is a result of analysis to determine the quality of the red wine based upon chemicals it consists of. The Smarten approach to datadiscovery is designed as an augmented analytics solution to serve business users.
This article provides a brief overview of random forest classification technique. Business Benefit: The predictive model will help us identify whether a customer fails to repay the loan depending on certain factors, which would lead to easier identification of risky customers and help the bank avert the risk delinquencies.
This article provides a brief overview of random forest classification technique. Business Benefit: The predictive model will help us identify whether a customer fails to repay the loan depending on certain factors, which would lead to easier identification of risky customers and help the bank avert the risk delinquencies.
This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business. Business Problem: A bank wants to find the correlation between income and credit card delinquency rate of credit card holders. What is the Karl Pearson Correlation Analytical Technique?
This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business. Business Problem: A bank wants to find the correlation between income and credit card delinquency rate of credit card holders. What is the Karl Pearson Correlation Analytical Technique?
This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business. Business Problem: A bank wants to find the correlation between income and credit card delinquency rate of credit card holders. What is the Karl Pearson Correlation Analytical Technique? About Smarten.
In this article, we discuss the analytical method known as frequent pattern mining, previously known as ‘association’ What is Frequent Pattern Mining? Use Case – 2 Business Problem: A bank-marketing manager wishes to analyze which products are frequently and sequentially bought together.
In this article, we discuss the analytical method known as frequent pattern mining, previously known as ‘association’ What is Frequent Pattern Mining? Use Case – 2 Business Problem: A bank-marketing manager wishes to analyze which products are frequently and sequentially bought together.
In this article, we discuss the analytical method known as frequent pattern mining, previously known as ‘association’ What is Frequent Pattern Mining? Business Problem: A bank-marketing manager wishes to analyze which products are frequently and sequentially bought together. Use Case – 2. About Smarten.
This article provides a brief explanation of the KMeans Clustering algorithm. KMeans Clustering is a grouping of similar things or data. How Does an Enterprise Use the KMeans Clustering Algorithm to Analyze Data? The Smarten approach to datadiscovery is designed as an augmented analytics solution to serve business users.
This article provides a brief explanation of the KMeans Clustering algorithm. KMeans Clustering is a grouping of similar things or data. How Does an Enterprise Use the KMeans Clustering Algorithm to Analyze Data? The Smarten approach to datadiscovery is designed as an augmented analytics solution to serve business users.
This article provides a brief explanation of the KMeans Clustering algorithm. KMeans Clustering is a grouping of similar things or data. How Does an Enterprise Use the KMeans Clustering Algorithm to Analyze Data? What is the KMeans Clustering algorithm? About Smarten.
This article summarizes our recent article series on the definition, meaning and use of the various algorithms and analytical methods and techniques used in predictive analytics for business users, and in augmented data preparation and augmented datadiscovery tools. About Smarten.
This article describes chi square test of association and hypothesis testing. This technique is used to determine if the relationship exists between any two business parameters that are of categorical data type. The Smarten approach to datadiscovery is designed as an augmented analytics solution to serve business users.
This article describes chi square test of association and hypothesis testing. This technique is used to determine if the relationship exists between any two business parameters that are of categorical data type. The Smarten approach to datadiscovery is designed as an augmented analytics solution to serve business users.
This article describes chi square test of association and hypothesis testing. This technique is used to determine if the relationship exists between any two business parameters that are of categorical data type. What is the Chi Square Test of Association Method of Hypothesis Testing? About Smarten.
This article will focus on the Naïve Bayes Classification method of analysis. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default”. It is useful for making predictions and forecasting data based on historical results.
This article will focus on the Naïve Bayes Classification method of analysis. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default”. It is useful for making predictions and forecasting data based on historical results.
This article will focus on the Naïve Bayes Classification method of analysis. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default”. It is useful for making predictions and forecasting data based on historical results. About Smarten.
In this article, we present a brief overview of compliance and regulations, discuss the cost of non-compliance and some related statistics, and the role data quality and data governance play in achieving compliance. In 2020 alone, banks were fined $14.2 million per incident in 2021, the highest in 17 years. (
This article summarizes our recent article series on the definition, meaning and use of the various algorithms and analytical methods and techniques used in predictive analytics for business users, and in augmented data preparation and augmented datadiscovery tools.
This article summarizes our recent article series on the definition, meaning and use of the various algorithms and analytical methods and techniques used in predictive analytics for business users, and in augmented data preparation and augmented datadiscovery tools.
2. Smarten SSDP (Self-Serve Data Preparation) truly makes Analytics Self-Serve! Smarten SSDP is a crucial component of Advanced DataDiscovery, enabling sophisticated features and functionality in an easy-to-use, intuitive, interactive environment that users will want to adopt and leverage. as the base.
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