"The solution is cross-validation. See https://www.datasciencecentral.com/page/search?q=cross+validation"
Prashanth Southekal, PhD's Discussions
Validation of the Prediction Model
Started this discussion. Last reply by Vincent Granville Aug 16. 3 Replies 1 Like
When there is a prediction model, apart from R-square, residuals etc. what are the different ways of performing validation of the prediction model? Basically,what are the different ways (apart from…Continue
Regression Analysis
Started this discussion. Last reply by Wayne G Fischer Feb 26, 2018. 10 Replies 1 Like
I am doing some regression analysis. Some of the independent variables are continuous while some are categorical. The dependent variable is continuous. Can you please help me on which regression…Continue
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Wasim replied to Prashanth Southekal, PhD's discussion Validation of the Prediction Model"Model evaluation and validation measures vary depending on the modelling technique you use. "
eric Shi replied to Prashanth Southekal, PhD's discussion Validation of the Prediction Model"when you validate a model, you should first consider model use fit the intended business purpose or not. Is the method used appropriate for the question, is the data appropriate for the model, is the model parameter estimation consistent with…"
Validation of the Prediction Model
When there is a prediction model, apart from R-square, residuals etc. what are the different ways of performing validation of the prediction model? Basically,what are the different ways (apart from R-square, residuals etc.) where you are validating of your Analytics prediction model given that the real/actual values will be available only in future ?See More
Validation of the Prediction Model
When there is a prediction model, apart from R-square, residuals etc. what are the different ways of performing validation of the prediction model? Basically,what are the different ways (apart from R-square, residuals etc.) where you are validating of your Analytics prediction model given that the real/actual values will be available only in future ?See More
Data Standardization: The Core building block for Data Quality.
Data for Business Performance is using data in operations, compliance, and decision making. However, in most cases the available data in business enterprises is of poor quality. An article in Harvard Business Review (HBR) says – just 3% of the data in a business enterprise is of good quality. In this backdrop, what can be done to improve data quality? While there are many solutions to improve data quality, one option is to capture the important data entities i.e. master data using data…See More
Data Standardization: The Core building block for Data Quality.
Data for Business Performance is using data in operations, compliance, and decision making. However, in most cases the available data in business enterprises is of poor quality. An article in Harvard Business Review (HBR) says – just 3% of the data in a business enterprise is of good quality. In this backdrop, what can be done to improve data quality? While there are many solutions to improve data quality, one option is to capture the important data entities i.e. master data using data…See More
Profile Information
- Short Bio
- Prashanth Southekal brings over 20 years of Data and Information Management consulting/working for companies such as SAP AG, Shell, Apple, P&G, and General Electric. He has published two books on Information Management including the most recent "Data for Business Performance".
- Professional Status
- Executive Management
- Years of Experience:
- 20
- Your Company:
- DBP-Institute
- Industry:
- Consulting
- Your Job Title:
- Managing Principal
- Interests:
- Finding a new position, Networking, New venture, Recruiting, Other
Prashanth Southekal, PhD's Blog
Data Standardization: The Core building block for Data Quality.
Posted on May 8, 2019 at 1:30pm 0 Comments 0 Likes
Data for Business Performance is using data in operations, compliance, and decision making. However, in most cases the available data in business enterprises is of poor quality. An article in Harvard Business Review (HBR) says – just 3% of the data in a business enterprise is of good quality. In this backdrop, what can be done to improve data quality? While there are many solutions to improve data quality, one option is to capture the important data entities i.e. master data using data…
ContinueCan Lack of Data Always Provide Valuable Insights?
Posted on March 18, 2019 at 3:30am 0 Comments 0 Likes
Can Lack of Data Always Provide Valuable Insights?
Prashanth H Southekal and Matthew Joyce
Today, data – both structured and unstructured, is seen as the most valuable business asset to solve problems and improve productivity. An article in Forbes says every company today is a data company! However, we…
ContinueDemystifying the Term Actionable Insights in Analytics
Posted on January 14, 2019 at 10:30am 0 Comments 0 Likes
Demystifying the Term Actionable Insights in Analytics
Prashanth H Southekal and Matthew Joyce
These days, the term Actionable Insights has become one of the most common terms used in Analytics projects. It has been used so much that it has almost lost its relevance and meaning today. So, what exactly is Actionable Insights and how can you…
ContinueThe Key to Unlock Digital Transformation
Posted on November 12, 2018 at 5:30pm 0 Comments 0 Likes
Digital Transformation is exploiting digital technologies and data to enhance the firm’s business model. Unfortunately, a Forbes study says that 84% of the Digital Transformation initiatives fail. There are many reasons for this and one important reason is tied to the way businesses inherently operate. Basically, businesses exist to earn profits and driving profits or margins is…
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