Knowi Predictive Analytics brings machine learning capabilities to every Data Engineer.
Integrate machine learning into your analytics workflows and drive data directed actions.
The platform provides two options:
- Out-of-the-box predictive analytics capabilities that test a dataset against a variety of forecasting models to determine the model best suited to the data, with the least Sum of Absolute Errors (SAE).
- Built-in Predictive and Machine Learning algorithms that can be plugged into data workflows.
This post focuses on the first option above that takes a hands-on look at how it works. We’ll take monthly stock prices for Amazon to determine predicted values over a three month period starting in July in a few simple steps. No signup is required to follow along.
Models used include:
- Simple Exponential, Double Exponential, Triple Exponential Smoothing Models
- Moving Averages and Weighted Moving Averages
- Naive Forecasting Model
- Regression and Polynomial Regression Model
- Multiple Linear Regression Model
The monthly stock prices looks like this:
- 06/01/16, 719.14
- 05/01/16, 683.85
- 04/01/16, 598.00
- 03/01/16, 579.00
- 02/01/16, 574.81
- 01/05/16, 633.79
- 12/01/15, 679.36
- 11/2/15, 628.35
- 10/1/15, 625.90
- 9/1/15, 511.89
- 8/3/15, 512.89
- 7/1/15, 536.15
- 6/1/15, 434.09
- 5/1/15, 429.23
- 4/1/15, 421.78
- 3/2/15, 372.10
- 2/2/15, 380.16
- 1/2/15, 354.53
1. Copy and paste the above dataset into https://www.knowi.com/csv-json-files-analytics.
2. Click on Show me. The data will be parsed and visualized immediately.
3. To perform predictions:
i. Click on Analyze from the menu of the time series chart. This opens up an Analysis mode.
ii. Drag date into the Grouping field.
iii. Click on ‘Add a derived Field’ option. Enter a name (“Predictions”, for example) and in the operation, enter predict(price,date,07/01/2016,1m,3). This will choose the best model based on historical accuracy of the model to determine the projected prices over a three month period, on a monthly basis.
That’s it! In a few simple steps, you can apply predictive analytics on any of your own datasets. Enjoy!
To get started with Knowi Predictive Analytics head to https://knowi.com and try it out free.
Additional Machine Learning Resources:
Predictive Analysis docs: https://docs.knowi.com/hc/en-us/articles/115006493407-Predictive-Analytics-Forecasting
Advanced Machine Learning (AI) Capabilities: https://knowi.com/adaptive-intelligence-machine-learning
All Documentation: https://docs.knowi.com