7504aa34cf
Add additional categorical features (uncomment).
2022-11-28 13:42:46 +01:00
9a218c8e2a
Add a script for two class train test split clustering classification.
2022-11-25 14:44:11 +01:00
98f78d72fc
Create a classification models class and use it in the ml pipeline script.
2022-11-25 12:35:45 +01:00
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
ddde80b421
Add classification with clustering ml pipeline script.
2022-11-24 09:24:13 +01:00
7afef5582f
Add TEMP lime_survey cols
2022-11-22 14:44:33 +01:00
183758cd37
Improve general ml classification pipeline script.
2022-11-22 14:31:49 +01:00
40029a8205
Add a script for ml classification pipeline.
2022-11-21 14:47:19 +01:00
ae0f54ecc2
Combine different segment scripts and set ml pipeline as a regression problem.
2022-11-21 11:41:11 +01:00
8defb271c9
Extend ml pipeline scripts with two additional CV methods.
2022-11-21 11:23:47 +01:00
b59798df26
Add a new file tailored for stressfulness event regression.
2022-11-16 14:49:40 +01:00
87ebb9f296
Delete files ... add to gitignore
2022-11-16 11:08:03 +01:00
1d8dcf8b21
Add 30 min features data and modify script.
2022-11-02 15:16:19 +01:00
9f7fa0c8e0
Add 18 hour daily data and slightly modify jupyter script.
2022-10-18 10:29:59 +02:00
cdff4da930
Merge branch 'ml_pipeline' of https://repo.ijs.si/junoslukan/straw2analysis into ml_pipeline
2022-10-17 22:15:17 +02:00
ad5f50babe
Correctly imputed data uploaded on STRAW (all targets)
2022-10-12 12:48:10 +02:00
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
27b2282ee0
Datasets (phone&E4 features) and Jupyter script of regression models.
2022-08-24 16:18:40 +02:00
a8fd96d2f1
Add analysis using RAPIDS.
2022-08-23 16:41:41 +02:00
e33a49c9fc
Add a demo of pipeline.
2021-11-17 10:44:49 +01:00
d34c2ec5e9
Merge branch 'ambient' into ml_pipeline
2021-11-17 10:39:55 +01:00
005b09cfdf
[WIP] Fix tests to use pyprojroot.
2021-10-29 12:07:12 +02:00
6fc0d962ae
Remove low values of pressure.
2021-10-22 18:09:17 +02:00
92fbda242b
Explore barometer and temperature data.
...
Add docstrings to models.
2021-10-14 17:59:33 +02:00
6302a0f0d9
Merge ambient sensors into one file.
...
Explore barometer sensor data for one phone.
2021-10-13 16:57:38 +02:00
a63a7eac99
[WIP] Add a test for SensorFeatures.
...
Additional analysis for adherence.
Small corrections.
2021-10-13 13:39:58 +02:00
b8c7606664
Add an option to read cached labels from a file.
2021-09-15 15:45:49 +02:00
ed062d25ee
Add export capabilities to labels.py.
2021-09-15 15:36:36 +02:00
20748890a8
Further refactor by moving helper functions.
2021-09-15 15:14:54 +02:00
28699a0fdf
Enable reading features from csv files.
2021-09-14 17:42:34 +02:00
af9e81fe40
Document the SensorFeatures class and its __init__ method.
2021-09-13 17:43:47 +02:00
b19eebbb92
Refactor machine_learning/pipeline.py by defining one class by file.
2021-09-13 11:41:57 +02:00
c1bb4ddf0f
Save calculated features to csv files.
2021-08-23 16:36:26 +02:00
0152fbe4ac
Delete the leftover class.
...
Add more prints.
2021-08-23 16:09:23 +02:00
3611fc76f7
Fill NaNs after merging all features.
2021-08-21 19:48:57 +02:00
ee30c042ea
Fill NaNs introduced in merge for proximity.
2021-08-21 19:40:42 +02:00
a71e132edf
Prepare the first full pipeline.
2021-08-21 19:04:09 +02:00
24c4bef7e2
Print some more messages.
2021-08-21 19:03:44 +02:00
11381d6447
Add some print statements for monitoring progress.
2021-08-21 18:54:02 +02:00
d19995385d
Account for the case when there is no data for days with labels.
2021-08-21 18:49:57 +02:00
f73f86486a
Fill communication features with appropriate values.
2021-08-21 18:28:22 +02:00
aed73bb7ed
Add fill values for communication for rows with no calls/smses.
2021-08-21 18:17:58 +02:00
8507ff5761
Check for NaNs in the data, since sklearn.LinearRegression cannot handle them.
2021-08-21 17:46:00 +02:00
0b85ee8fdc
Merge branch 'master' into ml_pipeline
2021-08-21 17:37:45 +02:00
e2e268148d
Fill in 0.5 for undefined ratio.
...
When there are no calls and no smses (of a particular type), the ratio is undefined. But since their number is the same, I argue that the ratio can represent that with a 0.5, similarly to the case where no_calls_all = no_sms_all != 0.
2021-08-21 17:33:31 +02:00
00015a3b8d
Fill in zeroes when joining or unstacking.
...
If there are no calls or smses for a particular day, there is no corresponding row in the features dataframe. When joining these, however, NaNs were introduced. Since a value of 0 is meaningful for all of these features, replace NaNs with 0's.
2021-08-21 17:31:15 +02:00
065cd4347e
[WIP] Add a class for model validation.
2021-08-20 19:44:50 +02:00
0b98d59aad
Aggregate labels using grouping_variable.
2021-08-20 19:17:22 +02:00
08fdec34f1
Merge features into a common df.
...
But first, group communication by the grouping_variable.
2021-08-20 17:59:00 +02:00
72b16af75c
Make group_by consistent with communication.
2021-08-20 17:52:31 +02:00
Primoz
junos