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Predictive maintenance for Valmet's breast roll shaker
(2019)
Digitalization and the Industrial Internet of Things (IIoT) enables the collection and analysis of vast amounts of data. Big data is often not utilized optimally, especially when regarding the condition and maintenance of ...
Detection and data-driven root cause analysis of paper machine drive anomalies
(2019)
The Industrial Internet has increased interest in the collection and utilization of data. The latter has become easier due to increased computing power and the development of analytical methods. The goal of this thesis is ...
Analysis of production testing data and detecting abnormal behavior
(2020)
This thesis presents methods to improve production testing methods by applying unsupervised machine learning to find anomalies from the data collected during testing. These methods are applied to a real-world case with the ...
Ohjelmistoekosysteemin ISV-kumppaneiden klusterointi ja priorisointi
(2021)
Nykypäivän kovasti kilpailulla ohjelmistokehityksen markkinoilla asiakkaat vaativat yrityksiltä entistä enemmän personointia, kätevyyttä ja hyviä kokemuksia. Näihin vaatimuksiin ohjelmistoja tarjoavan yrityksen on helpompi ...
Selection and evaluation of relevant predictors for credit scoring in peer-to-peer lending with random forest based methods
(2020)
This study focuses on identifying the important predictor variables for credit scoring using an empirical case of peer-to-peer (P2P) lending data. It contributes to other existing papers that also studied the relevance of ...
Utilization of the internet of things and machine learning in digital development of predictive maintenance at Finnish pulp mills
(2020)
The topic of this thesis is the utilization of the internet of things and machine learning in digital development of predictive maintenance at Finnish pulp mills. This thesis examines the architecture and steps needed to ...
Predicting disease-specific survival of colorectal cancer patients using serum and tissue data : a comparison of statistical and machine learning techniques for survival analysis, imputation, and feature selection
(2022)
Globally colorectal cancer (CRC) is the third most common cancer. The incidence rates of CRC are rising, especially in high-income countries. In Finland CRC has one of the highest mortality rates compared to other cancers. ...
Pairs trading on high-frequency data using machine learning
(2020)
Pairs Trading is a well-known statistical arbitrage strategy where a couple of equities which prices have co-moved in the past is expected to do so in the future. The rationale behind it is simple: at some entry point, ...
Predicting sepsis in the intensive care unit using machine learning
(2020)
Sepsis is a major burden to modern hospitals in terms of cost and death. Sepsis is a condition that lacks a diagnostic test making it hard to detect timely even for experienced medical professionals. The objective of this ...
Use of machine learning in supply chain management : case study with DataRobot
(2021)
In this Master’s thesis, machine learning in supply chain management was studied. The goal of this thesis was to find out in which problems machine learning is suitable in the field of supply chain management and what are ...