MLP BLOG

Now, how to understand or try to visualize something that is beyond our comprehension? A 4D surface, three features and one variable...

#algebra #geometry #calculus #ai

f1 score from eigenvectors assuming positive curvature outperforms euclidean metrics, which gives a hint of reality in a curved space or non

Study of f1 Score with Sklearn Metrics in Curved Surfaces. Non Euclidean Geometry.

Data analysis with Sklearn for stock prices, new features for the new approach.

Formulas used in several other codes created by ML Perspective. Formulas and class definition in Python.

Markov chains to calculate price changes in multiple securities comparison tests and advanced statistics.

The Hyperspace is not Always Euclidean: Study of f1 Score with Sklearn Metrics, Grid Search - Part III (Google Colab)

Each frequency bin is treated as coordinate feature, then, the hyperplane has as many dimensions as classes are.

New version 2.1 on Google Colab released. More concise and processing-time saving.

The Python code can be accessed in this post. Details on the instantiation process, class objects, functions and other techniques used can b

On this first paid-post it is being released the key statistics for the most traded ETFs in the USA. As the securities with the most...

In part I of the stock market quotes estimator it was explained that even though stock prices are random, the variable ▲Price is not and...

As its name says it, the stock market quotes estimator is a machine learning program developed to estimate, with a probability, within...