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100 Commits (1516d1c0008a51f8d82605bd0191eb424e13c970)

Author SHA1 Message Date
junos 1516d1c000 Cluster by demand_control_ratio_quartile. 2023-01-04 18:16:14 +01:00
junos 525496418f Configure jupytext. 2022-12-07 16:22:41 +01:00
junos 12f2c927fa Merge branch 'ml_pipeline' of repo.ijs.si:junoslukan/straw2analysis into ml_pipeline 
# Conflicts:
#	exploration/ml_pipeline_daily.py - deleted
 2022-12-07 15:36:52 +01:00
Primoz cf0e4f89be Test nonstandardized data with regular classification pipeline. 2022-11-29 14:06:06 +01:00
Primoz 7504aa34cf Add additional categorical features (uncomment). 2022-11-28 13:42:46 +01:00
Primoz 9a218c8e2a Add a script for two class train test split clustering classification. 2022-11-25 14:44:11 +01:00
Primoz 98f78d72fc Create a classification models class and use it in the ml pipeline script. 2022-11-25 12:35:45 +01:00
Primoz 218b684514 Automize clustering classification logic and add parameters at the begining of the scripts. General changes and improvements. 2022-11-24 16:12:20 +01:00
Primoz ddde80b421 Add classification with clustering ml pipeline script. 2022-11-24 09:24:13 +01:00
Primoz 7afef5582f Add TEMP lime_survey cols 2022-11-22 14:44:33 +01:00
Primoz 183758cd37 Improve general ml classification pipeline script. 2022-11-22 14:31:49 +01:00
Primoz 40029a8205 Add a script for ml classification pipeline. 2022-11-21 14:47:19 +01:00
Primoz ae0f54ecc2 Combine different segment scripts and set ml pipeline as a regression problem. 2022-11-21 11:41:11 +01:00
Primoz 8defb271c9 Extend ml pipeline scripts with two additional CV methods. 2022-11-21 11:23:47 +01:00
junos 848416bf6a Merge branch 'master' into ml_pipeline 
# Conflicts:
#	.gitignore
#	rapids
 2022-11-16 17:46:01 +01:00
Primoz b59798df26 Add a new file tailored for stressfulness event regression. 2022-11-16 14:49:40 +01:00
Primoz 1d8dcf8b21 Add 30 min features data and modify script. 2022-11-02 15:16:19 +01:00
Primoz 9f7fa0c8e0 Add 18 hour daily data and slightly modify jupyter script. 2022-10-18 10:29:59 +02:00
Primoz 466cd3dc23 Processing of a newly cleaned script. Addition of two ML models. And modifications with one hot encoding. 2022-10-10 16:47:00 +02:00
junos 2d2f0b916f Prepare a function to run all models from an input. 2022-08-31 18:46:14 +02:00
junos 8b8d626cf0 Merge branch 'ml_pipeline' into rapids 
# Conflicts:
#	exploration/ex_ml_pipeline.py
 2022-08-31 16:20:11 +02:00
Primoz 27b2282ee0 Datasets (phone&E4 features) and Jupyter script of regression models. 2022-08-24 16:18:40 +02:00
junos a8fd96d2f1 Add analysis using RAPIDS. 2022-08-23 16:41:41 +02:00
junos e177b15058 Clean features across participants. 
Explore the best linear regression feature.
 2022-01-19 13:41:09 +01:00
junos 832eb6137e ML with RAPIDS and missing values. 2022-01-19 12:53:03 +01:00
junos 702b091d73 Read RAPIDS features and create columns. 2022-01-07 17:00:12 +01:00
junos de10269d36 Export categories and add csv. 2021-12-15 18:26:20 +01:00
junos 7e8e922d71 Debugging of RAPIDS. 2021-12-15 18:25:53 +01:00
junos c4aacfffe1 Debug a ValueError in RAPIDS and add demo. 2021-12-15 16:03:49 +01:00
junos e33a49c9fc Add a demo of pipeline. 2021-11-17 10:44:49 +01:00
junos d34c2ec5e9 Merge branch 'ambient' into ml_pipeline 2021-11-17 10:39:55 +01:00
junos 92fbda242b Explore barometer and temperature data. 
Add docstrings to models.
 2021-10-14 17:59:33 +02:00
junos 6302a0f0d9 Merge ambient sensors into one file. 
Explore barometer sensor data for one phone.
 2021-10-13 16:57:38 +02:00
junos b8c7606664 Add an option to read cached labels from a file. 2021-09-15 15:45:49 +02:00
junos ed062d25ee Add export capabilities to labels.py. 2021-09-15 15:36:36 +02:00
junos 28699a0fdf Enable reading features from csv files. 2021-09-14 17:42:34 +02:00
junos af9e81fe40 Document the SensorFeatures class and its __init__ method. 2021-09-13 17:43:47 +02:00
junos b19eebbb92 Refactor machine_learning/pipeline.py by defining one class by file. 2021-09-13 11:41:57 +02:00
junos c1bb4ddf0f Save calculated features to csv files. 2021-08-23 16:36:26 +02:00
junos 065cd4347e [WIP] Add a class for model validation. 2021-08-20 19:44:50 +02:00
junos 0b98d59aad Aggregate labels using grouping_variable. 2021-08-20 19:17:22 +02:00
junos 08fdec34f1 Merge features into a common df. 
But first, group communication by the grouping_variable.
 2021-08-20 17:59:00 +02:00
junos 72b16af75c Make group_by consistent with communication. 2021-08-20 17:52:31 +02:00
junos d6337e82ac Merge branch 'master' into ml_pipeline 2021-08-20 17:43:53 +02:00
junos 9a319ac6e5 Add an option to group on other than just participant_id. 2021-08-20 17:41:12 +02:00
junos 6592612db7 Add a similar class for labels. 2021-08-19 17:44:04 +02:00
junos 5be3e82797 Accept nested feature configuration. 
To do this, pass a dict as parameters to SensorFeatures class, rather than actually reading the object from yaml file.
 2021-08-19 17:23:23 +02:00
junos 429aa43bd1 Add communication features to pipeline. 2021-08-19 17:05:44 +02:00
junos 0ed34e97b3 Convert the class into a YAML object. 
Add an example config file and demonstrate its usage in ex_ml_pipeline.ipynb.
 2021-08-19 16:31:42 +02:00
junos b06ec6e1ae [WIP] Methods to get the labels and data plus aggregate them. 2021-08-12 19:07:14 +02:00