Sökning: "overfitting"
Visar resultat 1 - 5 av 87 uppsatser innehållade ordet overfitting.
1. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods
Kandidat-uppsats, Lunds universitet/Statistiska institutionenSammanfattning : 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. LÄS MER
2. IDENTIFYING HATE SPEECH IN SOCIAL MEDIA THROUGH CONTENT AND SOCIAL CONNECTIONS ANALYSIS
Master-uppsats, Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteoriSammanfattning : 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. LÄS MER
3. Predicting Patent Data using Wavelet Regression and Bayesian Machine Learning
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : 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. LÄS MER
4. Aktiemarknadsprognoser: En jämförande studie av LSTM- och SVR-modeller med olika dataset och epoker
Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)Sammanfattning : Predicting stock market trends is a complex task due to the inherent volatility and unpredictability of financial markets. Nevertheless, accurate forecasts are of critical importance to investors, financial analysts, and stakeholders, as they directly inform decision-making processes and risk management strategies associated with financial investments. LÄS MER
5. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning models
Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologiSammanfattning : 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). LÄS MER