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Prediction

Predict the time series data

Give a data frame with these columns
Date
Close
2014-04-14
133.95
Base data can come from Yahoo driver
All
The model will predict SVR, LINEAR, ARIMA for 20 days on Close value
dataset = naas_drivers.yahoo.stock("TSLA")
pr = naas_drivers.prediction.get(dataset=dataset, prediction_type="all")
Prediction size
data_points:  The number of days in the future that are to predict.
dataset = naas_drivers.yahoo.stock("TSLA")
pr = naas_drivers.prediction.get(dataset=dataset, data_points=50)
Model
All the parameters of the above formula are explained below.
prediction_type:  The model to predict, it can be SVR, LINEAR, ARIMA, or all
dataset = naas_drivers.yahoo.stock("TSLA")
pr = naas_drivers.prediction.get(dataset=dataset, prediction_type="ARIMA")
Options
dataset : the dataset in DataFrame format
column: The exact name of the column that is to be predicted, from the dataset
date_column:The date range from the dataset. Will be used as the output index.
prediction_type: Can be ARIMA, LINEAR, SVR, COMPOUND or all
data_points **(optional):** number of days to predict
concact_label (optional): A column name who will generate a concatenated frame with past and future data.
dataset = naas_drivers.yahoo.stock("TSLA")
pr = naas_drivers.prediction.get(dataset=dataset)
Plot
Once you have predicted using the above predict formula, you can plot the predictions
  naas_drivers.plotly.stock(pr, , "linechart_close")
Check more options on the link below

NLP

Sentiment analysis