A comparative study between algorithms for time series forecasting on customer prediction : An investigation into the performance of ARIMA, RNN, LSTM, TCN and HMM

A comparative study between algorithms for time series forecasting on customer prediction : An investigation into the performance of ARIMA, RNN, LSTM, TCN and HMM

Time series prediction is one of the main areas of statistics and machine learning. In 2018 the two new algorithms higher order hidden Markov model and temporal convolutional network were proposed and emerged as challengers to the more traditional recurrent neural network and long-short term memory...

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Bibliographic Details
Main Author: Almqvist, Olof
Format: Others
Language:English
Published: Högskolan i Skövde, Institutionen för informationsteknologi 2019
Subjects:
machine learning
deep learning
time series forecasting
time series regression
data science
prediction
crisp-dm
keras
markov model
neural network
exploratory data analysis
maskininlärning
djupinlärning
tidsserieprediktion
tidsserieprognos
neurala nätverk
markovmodell
explorativ dataanalys
dataanalys
Engineering and Technology
Teknik och teknologier
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16974

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16974

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