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Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
The Electric Network Frequency (ENF) is the supply frequency of power distribution networks, which can be captured by multimedia signals recorded near electrical activities. It normally fluctuates slightly over time from its nominal value of 50 Hz/60 Hz. The ENF remain consistent across the entire power grid. This has led to the emergence of multiple forensic application like estimating the recording location and validating the time of recording. Recently an ENF based Machine Learning system was proposed which infers the region of recording from the power grids ENF signal extracted from the recorded multimedia signal, with the help of relevant features. In this work, we report some features novel to this application which serve as identifying characteristics for detecting the region of origin of the multimedia recording. In addition to the ENF variation itself, the utilization of the ENF harmonics pattern extracted from the media signals as novel features enables a more accurate identification of the region of origin. These characteristics were used in a multiclass machine learning implementation to identify the grid of the recorded signal.
"Machine learning and pattern recognition" labs & project @ Politecnico di Torino, a.y. 2020/2021.
Implementation of multinomial logisitic regression, Weighted Logistic Regression, Bayesian Logistic Regression, Gaussian Generative Classification and Gaussian Naive Bayes Classification from scratch in MATLAB
Python implementation for a Gaussian mixture model classifier!
Wine Dataset with Gaussian Classifier
Repository pertaining to traditional statistical methods being applied to foreground segmentation for an image of a Cheetah
Coded from scratch Carlini-Wagner attack on a Gaussian classifier to understand the popular adversarial attacks operation on a Gaussian classifier.
Italian Language Detection from Utterance Embeddings: A Comparative Study of SVM, Gaussian Models, Logistic Regression, and GMM. Made for the Machine Learning and Pattern Recognition course at Politecnico di Torino.
Predicting the volcanic eruption using ML Algorithms.
Classifiers to label images of handwritten digits. Includes KNN, Conditional Gaussian Classifier and Naive Bayes Classifier
Machine Learning model to predict heart disease using various patient parameters.
Image classification problem by classifying foreground and background regions in an image, using a Gaussian classifier
Python tools for classical machine learning, for when a deep neural net is just overkill
Python implementations of standard ML algorithms for classification, models evaluation and preprocessing.
Iris Dataset classification with Gaussian Classifiers. No ML Library, low level algorithms.
🌍🔥Predicting Reasons of Wildfires across US 50 States🌍🔥
Synthetic datasets generation for IGDA experiments