Essays about: "Machine learning prediction"

Showing result 1 - 5 of 785 essays containing the words Machine learning prediction.

  1. 1. Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques

    University essay from Lunds universitet/Matematisk statistik

    Author : Zeyuan Wu; [2024]
    Keywords : Machine Learning; Diagnosis of Sepsis; XGBoost; Logistic Regression; Mathematics and Statistics;

    Abstract : Sepsis, a serious medical condition often leading to patients requiring intensive care, has prompted numerous scientists to employ mathematical techniques to aid in its diagnosis. This thesis uses logistic regression and a machine learning technique, XGBoost, to predict true sepsis (as opposed to sepsis mimics) and culture-positive sepsis (among true sepsis) in critical care using blood test results, physiological measurements and other patient characteristics. READ MORE

  2. 2. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Nikolaos Staikos; [2024]
    Keywords : Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

    Abstract : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. READ MORE

  3. 3. 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

  4. 4. Learning a Grasp Prediction Model for Forestry Applications

    University essay from Umeå universitet/Institutionen för fysik

    Author : Elias Olofsson; [2024]
    Keywords : Forwarder; Autonomous grasping; Deep learning; Multibody dynamics; Convolutional neural network;

    Abstract : Since the advent of machine learning and machine vision methods, progress has been made in tackling the long-standing research question of autonomous grasping of arbitrary objects using robotic end-effectors. Building on these efforts, we focus on a subset of the general grasping problem concerning the automation of a forwarder. READ MORE

  5. 5. Data analytics and machine learning for railway track degradation: Using Bothnia Line track measurements for maintenance forecasting

    University essay from KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Author : Elie Roudiere; [2024]
    Keywords : Railway; Track geometry; Machine learning; Statistics; Predictive maintenance; Botniabanan; Järnväg; spårgeometri; maskininlärning; statistik; förebyggande underhåll; Botniabanan;

    Abstract : In this paper, a statistical method is developed to improve predictive maintenance on railway track. The problem tackled is being able to predict when the next maintenance event should take place to guarantee a certain track quality class. READ MORE