Hierarchical time series forecasting model using Gaussian Processes

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for luisroque from gravatar.com luisroque

Unverified details

These details have not been verified by PyPI
Meta
  • Author: Luis Roque
  • Tags python, time series, hierarchical, forecasting, gaussian process, machine learning
Classifiers

Project description

A package that allows you to forecast time series datasets with some type of hierarchical structure. The algorithm is implementedusing PyTorch

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for luisroque from gravatar.com luisroque

Unverified details

These details have not been verified by PyPI
Meta
  • Author: Luis Roque
  • Tags python, time series, hierarchical, forecasting, gaussian process, machine learning
Classifiers

Release history Release notifications | RSS feed

0.3.142

0.3.141

0.3.140

0.3.139

0.3.138

0.3.137

0.3.136

0.3.134

0.3.133

0.3.132

0.3.131

0.3.130

0.3.129

0.3.128

0.3.127

0.3.126

0.3.125

0.3.124

0.3.123

0.3.122

0.3.121

0.3.120

0.3.119

0.3.118

0.3.117

0.3.116

0.3.115

0.3.114

0.3.113

0.3.112

0.3.111

0.3.110

0.3.109

0.3.108

0.3.107

0.3.106

0.3.105

0.3.104

0.3.103

0.3.102

0.3.101

0.3.100

0.3.99

0.3.98

0.3.97

0.3.96

0.3.95

0.3.94

0.3.93

0.3.92

0.3.91

0.3.90

0.3.89

0.3.88

0.3.87

0.3.86

0.3.85

0.3.84

0.3.83

0.3.82

0.3.81

0.3.80

0.3.79

0.3.78

0.3.77

0.3.76

0.3.75

0.3.74

0.3.73

0.3.72

0.3.71

0.3.70

0.3.69

0.3.68

0.3.67

0.3.66

0.3.65

0.3.64

0.3.63

0.3.62

0.3.61

0.3.60

0.3.59

0.3.58

0.3.57

0.3.56

0.3.55

0.3.54

0.3.53

0.3.52

0.3.51

0.3.50

0.3.49

0.3.48

This version

0.3.47

0.3.46

0.3.45

0.3.44

0.3.43

0.3.42

0.3.41

0.3.40

0.3.39

0.3.38

0.3.37

0.3.36

0.3.35

0.3.34

0.3.33

0.3.32

0.3.31

0.3.30

0.3.29

0.3.28

0.3.27

0.3.26

0.3.25

0.3.24

0.3.22

0.3.21

0.3.20

0.3.19

0.3.18

0.3.17

0.3.16

0.3.15

0.3.14

0.3.13

0.3.12

0.3.11

0.3.10

0.3.9

0.3.8

0.3.7

0.3.6

0.3.5

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.9

0.2.8

0.2.6

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.9

0.1.8

0.1.7

0.1.6

0.1.3

0.1.2

0.1.1

0.1.0

0.0.9

0.0.8

0.0.7

0.0.6

0.0.5

0.0.4

0.0.3

0.0.2

0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gpforecaster-0.3.47.tar.gz (17.0 kB view details)

Uploaded Source

Built Distribution

gpforecaster-0.3.47-py3-none-any.whl (26.7 kB view details)

Uploaded Python 3

File details

Details for the file gpforecaster-0.3.47.tar.gz.

File metadata

  • Download URL: gpforecaster-0.3.47.tar.gz
  • Upload date:
  • Size: 17.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for gpforecaster-0.3.47.tar.gz
Algorithm Hash digest
SHA256 a1faab949119351f124df9b709229843aea73ed22bc40786f10f3c4fd2d7a6a0
MD5 99ce205b199aa5d1c188467dba1296ba
BLAKE2b-256 9a88f986ee4940617843fde23b3bbd61a1497774897b15c53ef3d162db8ca689

See more details on using hashes here.

File details

Details for the file gpforecaster-0.3.47-py3-none-any.whl.

File metadata

File hashes

Hashes for gpforecaster-0.3.47-py3-none-any.whl
Algorithm Hash digest
SHA256 e613bd5edd115c9751144c08815c232cee615b91cf7fff3db8b4aef043234a22
MD5 d48d77ab1648f7dd89b528b69226c688
BLAKE2b-256 c27277012008b404a291b4f4637e422eac529183ae273939d29d2bc594b74549

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page