Marko Niemelä

Apurahatutkija, tohtorin tutkinto

Yksikkö

Informaatioteknologian tiedekunta

Organisaatioyksikkö

Informaatioteknologian tiedekunta, Koulutusteknologia ja kognitiotiede

Sähköposti

marko.p.niemela@jyu.fi

Matkapuhelin

+358407189745

Tieteenalat

113 Tietojenkäsittely- ja informaatiotieteet

Julkaisut

Julkaisu

2024

Classification of dementia from spoken speech using feature selection and the bag of acoustic words model

Applied Computing and Intelligence.

Niemelä, Marko

von Bonsdorff, Mikaela

Äyrämö, Sami

Kärkkäinen, Tommi

Julkaisu

2022

Improving Clustering and Cluster Validation with Missing Data Using Distance Estimation Methods

Computational Sciences and Artificial Intelligence in Industry. Intelligent Systems, Control and Automation: Science and Engineering. Springer.

Niemelä, Marko

Kärkkäinen, Tommi

Julkaisu

2022

Internal cluster validation for data with missing values

JYU Dissertations.

Niemelä, Marko

Julkaisu

2022

Toolbox for Distance Estimation and Cluster Validation on Data With Missing Values

IEEE Access.

Niemelä, Marko

Äyrämö, Sami

Kärkkäinen, Tommi

Julkaisu

2020

Game learning analytics for understanding reading skills in transparent writing system

British Journal of Educational Technology.

Niemelä, Marko, Kärkkäinen, Tommi

Äyrämö, Sami

Ronimus, Miia

Richardson, Ulla

Lyytinen, Heikki

Julkaisu

2018

Comparison of cluster validation indices with missing data

European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. ESANN.

Niemelä, Marko

Äyrämö, Sami

Kärkkäinen, Tommi

Julkaisu

2017

Prediction of active peak force using a multilayer perceptron

Sports Engineering.

Niemelä, Marko

Kulmala, Juha-Pekka

Kauppi, Jukka-Pekka

Kosonen, Jukka

Äyrämö, Sami

Marko Niemelä

Classification of dementia from spoken speech using feature selection and the bag of acoustic words model

Improving Clustering and Cluster Validation with Missing Data Using Distance Estimation Methods

Internal cluster validation for data with missing values

Toolbox for Distance Estimation and Cluster Validation on Data With Missing Values

Game learning analytics for understanding reading skills in transparent writing system

Comparison of cluster validation indices with missing data

Prediction of active peak force using a multilayer perceptron

Human and Machine based Intelligence in Learning (Humble)