Commit From AutoTrain
Browse files- .gitattributes +3 -0
- README.md +45 -0
- config.json +1 -0
- model.joblib +3 -0
.gitattributes
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README.md
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---
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tags:
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- autotrain
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- tabular
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- regression
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- tabular-regression
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datasets:
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- Fatihrizkia/autotrain-data-xauusdh4timestamp
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co2_eq_emissions:
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emissions: 7.055812310656196
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---
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# Model Trained Using AutoTrain
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- Problem type: Single Column Regression
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- Model ID: 100145147571
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- CO2 Emissions (in grams): 7.0558
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## Validation Metrics
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- Loss: 0.380
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- R2: 0.421
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- MSE: 0.145
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- MAE: 0.302
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- RMSLE: 0.267
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## Usage
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```python
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import json
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import joblib
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import pandas as pd
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model = joblib.load('model.joblib')
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config = json.load(open('config.json'))
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features = config['features']
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# data = pd.read_csv("data.csv")
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data = data[features]
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data.columns = ["feat_" + str(col) for col in data.columns]
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predictions = model.predict(data) # or model.predict_proba(data)
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```
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config.json
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{"features": ["Unnamed: 0", "Time", "Open", "High", "Low", "Close", "Volume", "Pivot", "R1", "R2", "R3", "S1", "S2", "S3", "EMA_5", "EMA_50", "EMA_100", "EMA_200", "ADX", "+DMI", "-DMI", "RSI_14", "ATR_14", "Pivot_Touched", "R1_Touched", "R2_Touched", "R3_Touched", "S1_Touched", "S2_Touched", "S3_Touched", "Pivot_Position", "Breakout_High", "Breakout_Low", "Breakout_HighLow", "ADX_Sideways", "DMI_Bull_Cross", "DMI_Bear_Cross", "EMA100_Bearish_Position", "EMA100_Bullish_Position", "EMA200_Bearish_Position", "EMA200_Bullish_Position", "RSI14_Bullish_status", "RSI14_Bearish_status", "ATR14_complete"], "targets": ["target"], "model_type": "xgboost", "target_mapping": {}}
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model.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:a8b733cc8e8aa90001cfcf867af4e40a52c1f2e0478d669f37221bf31f54fd43
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size 523194
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