Predict is the core of the Akkio platform. Providing AI-powered forecasting for your BI needs. Here, you build an AI model to make predictions on your connected data.
This will take you to a selection page with the following options:
- Predict - Predict outcomes for data based on categories and numerical values. These predictions can be boolean or numerical. Examples are lead scoring, housing prices, employee attrition, etc.
- Forecast (Time Series) - Forecast time-dependent outcomes based on historical data with time information. See sales projections based on time of year, temperature ranges based on season, energy usage, etc.
Select what field you want to predict; each flow can only predict one column at a time. Select the 'Ignore' tab to ignore any fields that may lead to erroneous models. These can be anything from calculated to status columns.
The “Training Mode” section gives you several options for model training:
- High quality
- Higher quality
The quality options are ordered in the time taken to train. This won’t necessarily lead to higher accuracy due to a phenomenon known as “overfitting,” when a machine learning model only learns the training data well but does not generalize to new data.
- Restrict Range - Restrict the range of values predicted to values in the training dataset. For example, if you predict a discrete set of integers, you may want to ensure the model does not find partial values.
- Automatic Retraining - Retrains the model when the input dataset changes. This can ensure that when live data is connected, the model is always retrained on the most current version of the dataset.
Once happy with your settings, you can press 'Create Predictive Model.'