--- title: "#classification articles | Hashnode" description: "Explore 154 articles tagged #classification on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/classification" --- Tag # #classification 154 posts · 8 followers [Vashni Roy](https://hashnode.com/@vashniroy) · [3d ago](https://hashnode.com/posts/why-0-5-isn-t-always-the-right-classification-threshold/6af2ffa99538fc7c0f2ddfef) ### [Why 0.5 Isn't Always the Right Classification Threshold](https://vashniroy.hashnode.dev/why-0-5-isn-t-always-the-right-classification-threshold?utm_source=hashnode&utm_medium=feed) I changed the threshold of the same churn model from 0.3 to 0.7. The model stayed the same, but its predictions changed quite a lot. 3 min read · [vashniroy.hashnode.dev](https://vashniroy.hashnode.dev/why-0-5-isn-t-always-the-right-classification-threshold?utm_source=hashnode&utm_medium=feed) [Siddhesh Sawant](https://hashnode.com/@siddheshsawant) · [2d ago](https://hashnode.com/posts/logistic-regression-from-first-principles/6af340fb4f49d259cfecfa43) ### [Logistic Regression from First Principles: Log-Odds, Likelihood and the Decision Threshold](https://siddheshsawant.hashnode.dev/logistic-regression-from-first-principles?utm_source=hashnode&utm_medium=feed) Logistic regression derived step by step: sigmoid and log-odds, log loss and its gradient, gradient descent and Newton's method, and the decision threshold. 53 min read · [siddheshsawant.hashnode.dev](https://siddheshsawant.hashnode.dev/logistic-regression-from-first-principles?utm_source=hashnode&utm_medium=feed) [Dylan Hogg](https://hashnode.com/@dylanhogg) · [Sep 25](https://hashnode.com/posts/practical-guide-to-model2vec/6ab5dcb4e7fbb1e913b733eb) ### [Static embeddings: a practical guide to model2vec](https://infocruncher.hashnode.dev/practical-guide-to-model2vec?utm_source=hashnode&utm_medium=feed) Sentence-transformer embeddings work well, but they are slow on a CPU. For a few thousand texts, the speed doesn't matter. When you embed millions of texts, or need embeddings within a tight latency b 8 min read · [infocruncher.hashnode.dev](https://infocruncher.hashnode.dev/practical-guide-to-model2vec?utm_source=hashnode&utm_medium=feed) [Munukutla Sri Shanmukha Aditya](https://hashnode.com/@m-s-shanmukha-aditya) · [Sep 4](https://hashnode.com/posts/why-accuracy-can-be-misleading-in-failure-detection-systems/6a9b006c56ada066e5721232) ### [Why Accuracy Can Be Misleading in Failure Detection Systems](https://shanmukha-aditya.hashnode.dev/why-accuracy-can-be-misleading-in-failure-detection-systems?utm_source=hashnode&utm_medium=feed) Why accuracy can mislead in failure detection systems, and why precision and recall matter when working with imbalanced data. 4 min read · [shanmukha-aditya.hashnode.dev](https://shanmukha-aditya.hashnode.dev/why-accuracy-can-be-misleading-in-failure-detection-systems?utm_source=hashnode&utm_medium=feed) [1](https://hashnode.com/posts/why-accuracy-can-be-misleading-in-failure-detection-systems/6a9b006c56ada066e5721232) [Tharun](https://hashnode.com/@tharun-pandya) · [Aug 31](https://hashnode.com/posts/from-lines-to-decisions-why-regression-fails-at-classification/6a95d4e6626ac941e43dfc2f) ### [From Lines to Decisions: Why Regression Fails at Classification](https://tharunpandya.hashnode.dev/from-lines-to-decisions-why-regression-fails-at-classification?utm_source=hashnode&utm_medium=feed) Learn why linear regression fails at classification, how predictions can go below 0 or above 1, and why sigmoid is needed for probabilities. 9 min read · [tharunpandya.hashnode.dev](https://tharunpandya.hashnode.dev/from-lines-to-decisions-why-regression-fails-at-classification?utm_source=hashnode&utm_medium=feed) [Akash](https://hashnode.com/@irsakash) · [Aug 5](https://hashnode.com/posts/building-ml-models-from-data-to-deployment/6a736df7c41a5ed6cb4abd3b) ### [Building Production-Ready ML Models: From Data to Deployment](https://akashbuilds.hashnode.dev/building-ml-models-from-data-to-deployment?utm_source=hashnode&utm_medium=feed) Master ML workflows with real-world projects. Learn preprocessing, training, evaluation, and deployment using Python & scikit-learn. 12 min read · [akashbuilds.hashnode.dev](https://akashbuilds.hashnode.dev/building-ml-models-from-data-to-deployment?utm_source=hashnode&utm_medium=feed) [Nethmi Amasha](https://hashnode.com/@amasha) · [Aug 3](https://hashnode.com/posts/why-are-both-chi-square-test-and-anova-f-test-used-for-classification/6a705d7764f6f7cfb71d1762) ### [Why Are Both Chi-Square Test and ANOVA (F-Test) Used for Classification?](https://curiousdeveloperbyamasha.hashnode.dev/why-are-both-chi-square-test-and-anova-f-test-used-for-classification?utm_source=hashnode&utm_medium=feed) Explore the differences between Chi-Square and ANOVA (F-Test) for feature selection in classification using simple examples. 4 min read · [curiousdeveloperbyamasha.hashnode.dev](https://curiousdeveloperbyamasha.hashnode.dev/why-are-both-chi-square-test-and-anova-f-test-used-for-classification?utm_source=hashnode&utm_medium=feed) [Akshay Yadav](https://hashnode.com/@akshayyadav) · [Aug 1](https://hashnode.com/posts/predictive-maintenance-for-industrial-machines/6a6e0e351b07e2ccc6d12238) ### [Predictive Maintenance for Industrial Machines](https://projectsoncs.hashnode.dev/predictive-maintenance-for-industrial-machines?utm_source=hashnode&utm_medium=feed) Problem Statement A manufacturing plant wants to predict machine failure before it happens using live sensor readings (air/process temperature, rotational speed, torque, and tool wear), so that mainte 9 min read · [projectsoncs.hashnode.dev](https://projectsoncs.hashnode.dev/predictive-maintenance-for-industrial-machines?utm_source=hashnode&utm_medium=feed) [Aman Jain](https://hashnode.com/@aman454) · [Jul 16](https://hashnode.com/posts/building-a-gpt-model-from-scratch-part-5-fine-tuning-gpt-2-for-text-classification/6a5862af07144442ecc8ce4a) ### [Building a GPT Model from Scratch (Part 5): Fine-Tuning GPT-2 for Text Classification](https://curious-pm.hashnode.dev/building-a-gpt-model-from-scratch-part-5-fine-tuning-gpt-2-for-text-classification?utm_source=hashnode&utm_medium=feed) How I adapted a pretrained GPT-2 model to classify SMS messages as spam or not spam. 10 min read · [curious-pm.hashnode.dev](https://curious-pm.hashnode.dev/building-a-gpt-model-from-scratch-part-5-fine-tuning-gpt-2-for-text-classification?utm_source=hashnode&utm_medium=feed) [Rishikant](https://hashnode.com/@rishiii2) · [Jun 28](https://hashnode.com/posts/mastering-logistic-regression-probability-decision-boundaries-and-advanced-regularization/6a419083d33c94854b2c1e10) ### [Mastering Logistic Regression: Probability, Decision Boundaries, and Advanced Regularization](https://rishiii2.hashnode.dev/mastering-logistic-regression-probability-decision-boundaries-and-advanced-regularization?utm_source=hashnode&utm_medium=feed) Moving beyond basic classification: A deep dive into Cross-Entropy MLE, Elastic Net, and L-BFGS optimization. 7 min read · [rishiii2.hashnode.dev](https://rishiii2.hashnode.dev/mastering-logistic-regression-probability-decision-boundaries-and-advanced-regularization?utm_source=hashnode&utm_medium=feed)