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Found 13 papers, 1 papers with code
Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification
The polycystic ovary syndrome diagnosis is a problem that can be leveraged using prognostication based learning procedures.
Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis
Forgery of images is sub-category of image forensics and can be detected using Error Level Analysis.
Metric Effects based on Fluctuations in values of k in Nearest Neighbor Regressor
Regression branch of Machine Learning purely focuses on prediction of continuous values.
Performance Comparison of Simple Transformer and Res-CNN-BiLSTM for Cyberbullying Classification
In this paper we present a performance based comparison between simple transformer based network and Res-CNN-BiLSTM based network for cyberbullying text classification problem.
Prediction of Maneuvering Status for Aerial Vehicles using Supervised Learning Methods
Aerial Vehicles follow a guided approach based on Latitude, Longitude and Altitude.
Residual-Concatenate Neural Network with Deep Regularization Layers for Binary Classification
Many complex Deep Learning models are used with different variations for various prognostication tasks.
Res-CNN-BiLSTM Network for overcoming Mental Health Disturbances caused due to Cyberbullying through Social Media
Mental Health Disturbance has many reasons and cyberbullying is one of the major causes that does exploitation using social media as an instrument.
Detection of Tool based Edited Images from Error Level Analysis and Convolutional Neural Network
Image Forgery is a problem of image forensics and its detection can be leveraged using Deep Learning.
Combining Varied Learners for Binary Classification using Stacked Generalization
The Machine Learning has various learning algorithms that are better in some or the other aspect when compared with each other but a common error that all algorithms will suffer from is training data with very high dimensional feature set.
Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Method
High dimensional data for classification does create many difficulties for machine learning algorithms.
Effects of Parametric and Non-Parametric Methods on High Dimensional Sparse Matrix Representations
The semantics are derived from textual data that provide representations for Machine Learning algorithms.
Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognostication
A lot of prognostication methodologies have been formulated for early detection of Polycystic Ovary Syndrome also known as PCOS using Machine Learning.
Succinct Differentiation of Disparate Boosting Ensemble Learning Methods for Prognostication of Polycystic Ovary Syndrome Diagnosis
Prognostication of medical problems using the clinical data by leveraging the Machine Learning techniques with stellar precision is one of the most important real world challenges at the present time.
