---
license: mit
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
model_format: pickle
model_file: rf_model.pkl
widget:
structuredData:
x0:
- 22353.0
- 18097.0
- 1893.0
x1:
- 300.0
- 0.0
- 0.0
x10:
- 6.0
- 6.0
- 6.0
x11:
- 14.300000190734863
- 18.0
- 12.5
x12:
- 0.0
- 0.0
- 0.0
x13:
- -0.1458740234375
- -0.016845703125
- -0.145751953125
x14:
- 2574.0
- 2243.0
- 2393.0
x2:
- 1376.530029296875
- 1810.1199951171875
- 284.42999267578125
x3:
- 0.0
- 0.0
- 0.0
x4:
- 0.0
- 0.0
- 0.0
x5:
- 0.0
- 126.66000366210938
- 19.809999465942383
x6:
- 44.311378479003906
- 40.6067008972168
- 44.311378479003906
x7:
- 0.0
- 0.0
- 0.0
x8:
- 29.5
- 27.0
- 9.399999618530273
x9:
- 1.0
- 1.0
- 1.0
---
# Model description
[More Information Needed]
## Intended uses & limitations
[More Information Needed]
## Training Procedure
### Hyperparameters
The model is trained with below hyperparameters.
Click to expand
| Hyperparameter | Value |
|--------------------------|---------|
| bootstrap | True |
| ccp_alpha | 0.0 |
| class_weight | |
| criterion | gini |
| max_depth | |
| max_features | sqrt |
| max_leaf_nodes | |
| max_samples | |
| min_impurity_decrease | 0.0 |
| min_samples_leaf | 1 |
| min_samples_split | 2 |
| min_weight_fraction_leaf | 0.0 |
| n_estimators | 25 |
| n_jobs | -1 |
| oob_score | False |
| random_state | 1 |
| verbose | 0 |
| warm_start | False |
RandomForestClassifier(n_estimators=25, n_jobs=-1, random_state=1)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
RandomForestClassifier(n_estimators=25, n_jobs=-1, random_state=1)