Sanjayraju30 commited on
Commit
e30a662
·
verified ·
1 Parent(s): baacba5

Update risk_model.py

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Files changed (1) hide show
  1. risk_model.py +10 -2
risk_model.py CHANGED
@@ -2,11 +2,17 @@ import os
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  import pandas as pd
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  from sklearn.ensemble import RandomForestClassifier
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  from joblib import dump, load
 
 
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  MODEL_PATH = "heating_model.pkl"
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  DATA_PATH = "mantle_training.csv"
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  HISTORY = []
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  def train_and_save_model():
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  data = pd.read_csv(DATA_PATH)
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  X = data[["temperature", "duration"]]
@@ -27,13 +33,15 @@ def predict_risk(temp, duration):
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  global model
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  pred = model.predict([[temp, duration]])[0]
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  score = max(model.predict_proba([[temp, duration]])[0]) * 100
 
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  HISTORY.append({
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  "Temperature": temp,
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  "Duration": duration,
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  "Risk": pred,
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- "Confidence": round(score, 2)
 
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  })
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- return pred, round(score, 2)
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  def retrain_model():
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  try:
 
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  import pandas as pd
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  from sklearn.ensemble import RandomForestClassifier
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  from joblib import dump, load
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+ from datetime import datetime
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+ import pytz
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  MODEL_PATH = "heating_model.pkl"
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  DATA_PATH = "mantle_training.csv"
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  HISTORY = []
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+ def get_ist_time():
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+ ist = pytz.timezone('Asia/Kolkata')
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+ return datetime.now(ist).strftime("%Y-%m-%d %H:%M:%S %Z")
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+
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  def train_and_save_model():
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  data = pd.read_csv(DATA_PATH)
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  X = data[["temperature", "duration"]]
 
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  global model
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  pred = model.predict([[temp, duration]])[0]
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  score = max(model.predict_proba([[temp, duration]])[0]) * 100
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+ timestamp = get_ist_time()
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  HISTORY.append({
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  "Temperature": temp,
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  "Duration": duration,
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  "Risk": pred,
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+ "Confidence": round(score, 2),
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+ "Timestamp": timestamp
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  })
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+ return pred, round(score, 2), timestamp
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  def retrain_model():
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  try: