Search results for "klusterianalyysi"
showing 10 items of 31 documents
Motivators, barriers and strategies of weight management: A cross-sectional study among Finnish adults.
2018
Abstract Background Weight management (WM) is an ongoing global challenge. The purpose of this study was to analyze motivators, barriers, and strategies of WM among Finnish adults. Methods Data were collected in the ‘KULUMA’ (Consumers at the Weight Management Market) project among 667 community-dwelling adults in Eastern and Central Finland (Kuopio and Jyvaskyla). The self-reported questionnaire collected background information and responses to motivators, barriers, and strategy items. Principal component analysis (PCA) was used to extract components of motivators, barriers, and strategies of WM, along with K-means clustering to categorize the participants. Results About 55% of the respond…
Patterns of Eating and Physical Activity Attitudes and Behaviors in Relation to Body Mass Index
2016
The aim of the study was to identify and characterize the patterns of the psychological and behavioral characteristics, in relation to body mass index. In addition, the study examined the associations between the patterns and demographic characteristics, exercise, eating habits, and healthrelated psychological variables. Participants were 361 Greek adults, randomly selected and completed self-reported questionnaires. The surveys examined demographic characteristics, healthrelated psychological variables (attitudes and intentions toward exercise and healthy eating, perceived behavioral control, health locus of control, general health, self-control, and body image) and the behaviors of exerci…
Towards Evidence-Based Academic Advising Using Learning Analytics
2018
Academic advising is a process between the advisee, adviser and the academic institution which provides the degree requirements and courses contained in it. Content-wise planning and management of the student’ study path, guidance on studies and academic career support is the main joint activity of advising. The purpose of this article is to propose the use of learning analytics methods, more precisely robust clustering, for creation of groups of actual study profiles of students. This allows academic advisers to provide evidence-based information on the study paths that have actually happened similarly to individual students. Moreover, academic institutions can focus on management and upda…
Clustering ball possession duration according to players’ role in football small-sided games
2022
This study aimed to explore which offensive variables best discriminate the ball possession duration according to players specific role (defenders, midfielders, attackers) during a Gk+3vs3+Gk football small-sided games. Fifteen under-15 players (age 13.2±1.0 years, playing experience 4.2±1.0 years) were grouped according to their positions (team of defenders, n = 5; team of midfielders, n = 7; team of attackers, n = 3). On each testing day (n = 3), each team performed one bout of 5-min against each team in a random order, accounting for a total of nine bouts in the following scenarios: i) defenders vs midfielders; ii) defenders vs attackers; iii) midfielders vs attackers. Based on video, a …
Kansainvälisten koulutusarvioiden vertailu koulutuksellisen tiedonlouhinnan keinoin
2016
Koulutusta ja eri ikäisten lasten akateemista suorituskykyä mittaavat tutkimustulokset ovat kiinnostavaa tarkasteltavaa monien alojen työntekijöille ja tutkijoille. Nykyään monet organisaatiot, kuten OECD (Organisation for Economic Co-operation and Development) ja IEA (International Association for the Evaluation of Educational Achievement), järjestävät tietyin aikavälein kansainvälisiä mittauksia, joissa mitataan tietyn ikäisten lasten akateemisia kykyjä ja kysellään heidän elämästään koulussa ja kotona. Näistä mittauksista syntyvät tietokannat ovat suuria ja ne tarjoavat monipuolista tietoa koulutuksesta ja lasten oppimiseen vaikuttavista tekijöistä. Kaiken tämän lisäksi, nämä tietokannat…
Varttuneet kuluttajat ja wellness-teknologia : kehon arvottamisesta kohti omaehtoista käyttäjäkokemusta
2017
Yli 50-vuotiaat, varttuneet kuluttajat, ovat ostovoimainen ryhmä, jolla on mahdollisuus panostaa myös vapaa-aikaan. Kyseisen ikäryhmän sisäisiä eroja kulutuskäyttäytymisessä on kuitenkin tutkittu toistaiseksi vähän. Tässä tutkimuksessa selvitimme klusterianalyysin avulla, millaisia kuluttajaryhmiä varttuneiden kuluttajien joukosta löytyy vapaa-ajan kulutuksen suhteen. Lisäksi tarkastelimme, onko löytyneiden klustereiden välillä eroja hyvinvoinnissa. Tutkimuksessa käytettiin Suomi 2014 – Kulutus ja elämäntapa -tutkimuksen aineistoa 50–74-vuotiaiden (N=760) osalta. Klusterianalyysin perusteella varttuneet kuluttajat jakaantuivat kuuteen ryhmään vapaa-ajan kulutuksensa suhteen: säästeliäisiin,…
Exploring management control system typologies : an organisation-level view
2020
PurposeManagement controls are the processes and mechanisms managers use to influence the behaviour of individuals and groups towards the organisation’s objectives and goals. Discrete management controls and management control system (MCS) frameworks have been extensively researched, but there is little research on organisation-level MCS types. This study aims to identify organisation-level MCS types.Design/methodology/approachThis study draws on the MCS type literature, the competing values framework and the upper echelons theory to form organisation effectiveness and top management team constructs to characterise firms. Cluster analysis was used to group a sample of 318 firm-years into MC…
Two Overwatch Player Profiles
2022
AbstractWe pursue Overwatch player profiles via a statistical cluster analysis of survey data from the UK (N = 1089) and the USA (N = 417). The profiles are based on the players’ activity, challenge, and experiential preferences as well as motivations. Our analytical process produces six esports player clusters, two of which with Overwatch. The first (OW1) plays mainly Overwatch and Fortnite on a console, and they enjoy diverse types of non-competitive play elements more than other esports players. The second cluster (OW2) plays mainly Overwatch and League of Legends on a PC, and despite appearing more “competitive”, they did not report more competitive preferences. We suggest that the alle…
Scalable robust clustering method for large and sparse data
2018
Datasets for unsupervised clustering can be large and sparse, with significant portion of missing values. We present here a scalable version of a robust clustering method with the available data strategy. Moreprecisely, a general algorithm is described and the accuracy and scalability of a distributed implementation of the algorithm is tested. The obtained results allow us to conclude the viability of the proposed approach. peerReviewed
Comparison of cluster validation indices with missing data
2018
Clustering is an unsupervised machine learning technique, which aims to divide a given set of data into subsets. The number of hidden groups in cluster analysis is not always obvious and, for this purpose, various cluster validation indices have been suggested. Recently some studies reviewing validation indices have been provided, but any experiments against missing data are not yet available. In this paper, performance of ten well-known indices on ten synthetic data sets with various ratios of missing values is measured using squared euclidean and city block distances based clustering. The original indices are modified for a city block distance in a novel way. Experiments illustrate the di…