Essays about: "linjär regression"

Showing result 1 - 5 of 249 essays containing the words linjär regression.

  1. 1. ML implementation for analyzing and estimating product prices

    University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Author : Abel Getachew Kenea; Gabriel Fagerslett; [2024]
    Keywords : Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

    Abstract : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. READ MORE

  3. 2. Decision Trees for Classification of Repeated Measurements

    University essay from Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

    Author : Julianna Holmberg; [2024]
    Keywords : Repeated Measurement Data; Growth Curve Model; Linear Discriminant Analysis; Decision Tree; Bootstrap Aggregating; CART; CART-LC;

    Abstract : Classification of data from repeated measurements is useful in various disciplines, for example that of medicine. This thesis explores how classification trees (CART) can be used for classifying repeated measures data. READ MORE

  4. 3. Staff Shortage on SJ Trains

    University essay from KTH/Matematisk statistik

    Author : Casper Öberg; Nora Moro; [2023]
    Keywords : Multiple linear regression; Residual analysis; Multicollinearity; Staff shortage; Forecast; Trains; Multipel linjär regression; Residualanalys; Multikollinearitet; Personalbrist; Prognos; Tåg;

    Abstract : This thesis is a case study in collaboration with SJ AB, a government owned railway companyin Sweden. The employees aboard the trains are an essential part of operating thetrains efficiently. Therefore, it is vital to forecast absences well in order to avoid havingto cancel train trips or having employees work over time. READ MORE

  5. 4. Factors Affecting Employment Duration in the Food Retail Industry

    University essay from KTH/Matematisk statistik

    Author : Beata Sundling; Lova Höft; [2023]
    Keywords : statistics; applied mathematics; regression analysis; multiple linear regression; employment duration; employment turnover rate; food retail industry; statistik; tillämpad matematik; regressionsanalys; multipel linjär regression; anställningens varaktighet; personalomsättningshastighet; dagligvaruhandeln;

    Abstract : Measuring and tracking the employee turnover rate is a crucial part when evaluating a company’s performance. An important part of this is measuring the employment duration within an organization. READ MORE

  6. 5. Traffic State Estimation on Swedish Highways : Model Comparison using Multisource Data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Jiaqi Xu; [2023]
    Keywords : Traffic State Estimation; Macroscopic Traffic Model; Extended Kalman Filter; Particle Filter; Data Fusion; Trafiklägesuppskattning; Makroskopisk trafikmodell; Utökad Kalman-filter; Partikelfilter; Datafusion;

    Abstract : Due to the escalating demand for traffic information and management, the significance of traffic state estimation, which involves the assessment of traffic conditions on road segments with limited measurement data, is increasing. Two primary estimation methods are model-driven and data-driven. READ MORE