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---
tags:
- autotrain
- tabular
- classification
- tabular-classification
datasets:
- BrianDsouzaAI/autotrain-data-tab-multi
widget:
structuredData:
Planned_Stories:
- 10
- 20
- 30
Delivered_Stories:
- 11
- 12
- 13
co2_eq_emissions:
emissions: 2.067391665478424
---
# Model Trained Using AutoTrain
- Problem type: Multi-label Classification
- Model ID: 92337144714
- CO2 Emissions (in grams): 2.0674
## Validation Metrics
- Loss: 3.634
## Usage
```python
import json
import joblib
import numpy as np
import pandas as pd
models = joblib.load('model.joblib')
config = json.load(open('config.json'))
features = config['features']
# data = pd.read_csv("data.csv")
data = data[features]
data.columns = ["feat_" + str(col) for col in data.columns]
predictions = []
for model_ in models:
predictions_ = model_.predict(data) # or model.predict_proba(data)[:, 1]
predictions.append(predictions_)
predictions = np.column_stack(predictions)
``` |