| import pandas as pd |
| from prophet import Prophet |
| from sklearn.metrics import mean_absolute_error |
| import joblib |
| from utils.preprocessing import preprocess_data |
| from huggingface_hub import HfApi, login |
| import os |
|
|
| def train_time_series(): |
| """Train the time-series model for optimal posting times.""" |
| |
| df = pd.read_json("data/raw/engagement_metrics.json") |
| df = preprocess_data(df) |
|
|
| |
| time_series_data = df.groupby('posting_time').agg({'engagement_rate': 'mean'}).reset_index() |
| time_series_data = time_series_data.rename(columns={'posting_time': 'ds', 'engagement_rate': 'y'}) |
|
|
| |
| prophet_model = Prophet() |
| prophet_model.fit(time_series_data) |
|
|
| |
| joblib.dump(prophet_model, "prophet_model.pkl") |
|
|
