From be1f4be54fe4039fb66ede52574bd969c743ddd7 Mon Sep 17 00:00:00 2001 From: JulienPeloton Date: Tue, 3 Dec 2024 12:57:28 +0100 Subject: [PATCH] Update model documentation --- fink_science/data/models/README.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/fink_science/data/models/README.md b/fink_science/data/models/README.md index 5a5b7e37..a0c2aee5 100644 --- a/fink_science/data/models/README.md +++ b/fink_science/data/models/README.md @@ -2,6 +2,7 @@ To load and run model properly, you need to check carefuly the dependencies used in Fink: [deps](https://github.com/astrolabsoftware/fink-broker/tree/master/deps). +Information about the science modules (and related journal papers), can be found in the [Fink documentation](https://fink-broker.readthedocs.io/en/latest/broker/science_modules/). ## ZTF @@ -9,16 +10,15 @@ Default models used for ZTF: | model name | used in | Description | |------------|---------|-------------| -| `snn_models/snn_snia_vs_nonia/model.pt`| `snn` | Ia vs core-collapse SNe | -| `snn_models/snn_sn_vs_all/model.pt`| `snn` | SNe vs. anything else (var star and other stuff in training) | -| `default-model_sigmoid.obj` | `random_forest_snia` | Early SN Ia classification using lightcurve features (random forest). Binary classification. `sklearn==1.0.2` | -| `rf.sav` | `microlensing` | scikit-learn model used in Random Forest. `sklearn==1.0.2` | -| `pca.sav` | `microlensing` | scikit-learn (pca) model used in Random Forest. `sklearn==1.0.2` | -|`components.csv`| `kilonova`| file containing principal components from simulations| +| `snn_models/snn_snia_vs_nonia/model.pt`| `snn` | Binary classifier based on SuperNNova. Ia vs core-collapse SNe | +| `snn_models/snn_sn_vs_all/model.pt`| `snn` | Binary classifier based on SuperNNova. SNe vs. anything else (var star and other stuff in training) | +| `default-model_sigmoid.obj` | `random_forest_snia` | Early SN Ia classification using lightcurve features. Binary classification. Random forest. `sklearn==1.0.2` | +| `rf.sav` | `microlensing` | Random Forest classifier for microlensing classification. 4 classes: ML, VAR, CONST, SN. `sklearn==1.0.2` | +| `pca.sav` | `microlensing` | PCA for microlensing classification. `sklearn==1.0.2` | | `for_al_loop/*.pkl` | active learning loop | Models used in the context of Active Learning for early SN Ia detection. `sklearn==1.0.2` | -|`anomaly_detection`| `anomaly_detection` | Zip files with different models used for Anomaly detection | +|`anomaly_detection`| `anomaly_detection` | Zip files with different models used for Anomaly detection. Based on modified Random Forest. | -Models for Kilonova are in [kndetect](https://github.com/b-biswas/kndetect). +Models for Kilonova detection are in [kndetect](https://github.com/b-biswas/kndetect). ## Elasticc/Rubin