quadratic programming

Model Perspective

Dec 29, 2022 · Fundamentals

Build an Optimal Stock Portfolio with Markowitz Mean‑Variance Model in Python

This article explains how to model and solve a three‑stock portfolio optimization problem using Markowitz's mean‑variance framework, compute asset statistics with Python, and obtain the optimal allocation via quadratic programming.

Markowitz modelPythonfinance

0 likes · 6 min read

Build an Optimal Stock Portfolio with Markowitz Mean‑Variance Model in Python

Model Perspective

Aug 6, 2022 · Artificial Intelligence

How Kernel Functions Enable SVMs to Classify Non‑Linear Data

When training data from two classes overlap heavily, linear SVMs fail, so we map inputs into a high‑dimensional Hilbert (feature) space using kernel functions—such as linear, polynomial, radial basis, and Fourier kernels—to make the data linearly separable, formulate a quadratic programming problem, solve its convex dual, and construct a classifier for unknown samples.

Hilbert spaceMachine LearningSVM

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How Kernel Functions Enable SVMs to Classify Non‑Linear Data