{"id":229494,"date":"2026-06-10T12:30:00","date_gmt":"2026-06-10T16:30:00","guid":{"rendered":"https:\/\/testing.news-you-need.com\/index.php\/2026\/06\/10\/how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence\/"},"modified":"2026-06-10T13:30:27","modified_gmt":"2026-06-10T17:30:27","slug":"how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/testing.news-you-need.com\/index.php\/2026\/06\/10\/how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence\/","title":{"rendered":"How to Train a Scoring Model in the Age of Artificial Intelligence"},"content":{"rendered":"<p><a href=\"https:\/\/towardsdatascience.com\/how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence\/\">How to Train a Scoring Model in the Age of Artificial Intelligence<\/a><\/p>\n<p><a href=\"https:\/\/towardsdatascience.com\/how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence\/\">https:\/\/towardsdatascience.com\/how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence\/<\/a><\/p>\n<p>Publish Date: <a href=\"publish_date]\">2026-06-10 12:30:00<\/a><\/p>\n<p>Source Domain: <a href=\"towardsdatascience.com\">towardsdatascience.com<\/a><\/p>\n<p>Here is a distilled summary of the article in an unordered list:<\/p>\n<ul>\n<li>\n<p><strong>Modeling Framework<\/strong>: Focus on building robust scoring models using logistic regression, emphasizing multi-criteria model selection beyond mere performance metrics.<\/p>\n<\/li>\n<li>\n<p><strong>Tools and Datasets<\/strong>: Uses tools like Codex and datasets from Kaggle (credit scoring dataset). Datasets are split into training, test, and out-of-time samples for thorough model evaluation.<\/p>\n<\/li>\n<li>\n<p><strong>Variable Preparation<\/strong>: Explanatory variables are categorical and converted into dummy variables. Categories with higher default rates are deemed less risky, making interpretation easier.<\/p>\n<\/li>\n<li>\n<p><strong>Candidate Models<\/strong>: Train logistic regression models on different combinations of candidate variables, assessing multiple criteria including statistical validation, business consistency, discrimination power, stability, interpretability, and multicollinearity.<\/p>\n<\/li>\n<li>\n<p><strong>Performance Metrics<\/strong>: Evaluate models using discrimination metrics like ROC, AUC, and Gini as well as precision-recall metrics, considering class imbalance and prediction quality.<\/p>\n<\/li>\n<li>\n<p><strong>Stability Evaluation<\/strong>: Assess model stability across different samples (training, test, and out-of-time) and introduce penalized Gini criterion to gauge consistency.<\/p>\n<\/li>\n<li>\n<p><strong>Model Selection<\/strong>: Choose the model that strikes a balance between performance, stability, interpretability, simplicity, and business consistency. A four-variable model with satisfactory validation criteria and discriminatory power is selected.<\/p>\n<\/li>\n<li>\n<p><strong>Assistance from AI<\/strong>: Use of Codex to automate repetitive tasks such as code generation, model estimation, and reporting but maintain human oversight for statistical validation and business logic adherence.<\/p>\n<\/li>\n<li>\n<p><strong>Results Presentation<\/strong>: Illustrate the model selection process&#8217;s transparency and present detailed statistical and graphical analyses to justify the final model choice.<\/p>\n<\/li>\n<\/ul>\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>How to Train a Scoring Model in the Age of Artificial Intelligence https:\/\/towardsdatascience.com\/how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence\/ Publish Date:&#8230;<\/p>\n","protected":false},"author":1,"featured_media":229495,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/towardsdatascience.com\/wp-content\/uploads\/2026\/06\/ChatGPT-Image-6-juin-2026-22_45_01.jpg","fifu_image_alt":"","footnotes":""},"categories":[14],"tags":[20],"class_list":["post-229494","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","tag-artificial-intelligence"],"_links":{"self":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/229494"}],"collection":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/comments?post=229494"}],"version-history":[{"count":1,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/229494\/revisions"}],"predecessor-version":[{"id":229496,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/posts\/229494\/revisions\/229496"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/media\/229495"}],"wp:attachment":[{"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/media?parent=229494"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/categories?post=229494"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/testing.news-you-need.com\/index.php\/wp-json\/wp\/v2\/tags?post=229494"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}