Essays about: "Overfitting"
Showing result 1 - 5 of 83 essays containing the word Overfitting.
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1. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods
University essay from Lunds universitet/Statistiska institutionenAbstract : As the amount of high dimensional data becomes increasingly accessible and common, the need for reliable methods to combat problems such as overfitting and multicollinearity increases. Models need to be able to manage large data sets where predictor variables often outnumber the amount of observations. READ MORE
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2. IDENTIFYING HATE SPEECH IN SOCIAL MEDIA THROUGH CONTENT AND SOCIAL CONNECTIONS ANALYSIS
University essay from Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteoriAbstract : Hate speech is a problem which puts its targets at risk of serious harm. It spreads fast and has a real influence on the society because of the ubiquity of the internet and social media, and so various research efforts have been put to find solutions to automatic hate speech detection. READ MORE
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3. Predicting Patent Data using Wavelet Regression and Bayesian Machine Learning
University essay from KTH/Matematik (Avd.)Abstract : Patents are a fundamental part of scientific and engineering work, ensuringprotection of inventions owned by individuals or organizations. Patents areusually made public 18 months after being filed to a patent office, whichmeans that current publicly available patent data only provides informationabout the past. READ MORE
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4. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning models
University essay from Högskolan i Skövde/Institutionen för informationsteknologiAbstract : A key challenge for maximizing the world’s food supply is crop yield prediction. In this study, three machine models are used to predict the fresh weight (yield) of lettuce plants that are grown inside indoor farms hydroponically using the vertical farming infrastructure, namely, support vector regressor (SVR), random forest regressor (RFR), and deep neural network (DNN). READ MORE
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5. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods
University essay from KTH/FysikAbstract : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). READ MORE