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© Algolytics. All rights reserved. 1
Creating Predictive
Models Automatically
AUTOMATIC BUSINESS MODELER by
© Algolytics. All rights reserved. 2
Overview of ABM tool
automatically builds accurate and
interpretable predictive models
© Algolytics. All rights reserved. 3
EXAMPLARY APPLICATIONS
Selecting customers likely
to stop using the company’s products
(churners)
© Algolytics. All rights reserved. 4
EXAMPLARY APPLICATIONS
Selecting customers likely
to stop using the company’s products
(churners)
Assessing creditworthiness
of a debtor (Credit scoring)
© Algolytics. All rights reserved. 5
EXAMPLARY APPLICATIONS
Selecting customers likely
to stop using the company’s products
(churners)
Assessing creditworthiness
of a debtor (Credit scoring)
Assessing the probability of the
response to a marketing
campaign (targeting)
© Algolytics. All rights reserved. 6
EXAMPLARY APPLICATIONS
Selecting customers likely
to stop using the company’s products
(churners)
Assessing creditworthiness
of a debtor (Credit scoring)
Assessing the probability of the
response to a marketing
campaign (targeting)
Predicting offer take-up –
selecting offers most likely to be
accepted by customers
© Algolytics. All rights reserved. 7
EXAMPLARY APPLICATIONS
Selecting customers likely
to stop using the company’s products
(churners)
Assessing creditworthiness
of a debtor (Credit scoring)
Assessing the probability of the
response to a marketing
campaign (targeting)
Predicting offer take-up –
selecting offers most likely to be
accepted by customers
Lead scoring…
© Algolytics. All rights reserved. 8
EXAMPLARY APPLICATIONS
…tell us about your project
and we’ll advice you on predictive models use
Selecting customers likely
to stop using the company’s products
(churners)
Assessing creditworthiness
of a debtor (Credit scoring)
Assessing the probability of the
response to a marketing
campaign (targeting)
Predicting offer take-up –
selecting offers most likely to be
accepted by customers
Lead scoring…
support_abm @ algolytics.pl
click to email us
© Algolytics. All rights reserved. 9
Automates activities, like fast variable
selection, interaction and transformations of variables or best
model selection
Provides 3 working modes presenting different
approaches to data processing and modeling
Handles prediction and
classification problems
WHAT ABM DOES
© Algolytics. All rights reserved. 10
Available via an easy-to-use SaaS web-based
interface. No need to install
anything
Provides data scoring Generates detailed
reports for each stage of the model building
Automates activities, like fast variable
selection, interaction and transformations of variables or best
model selection
Provides 3 working modes presenting different
approaches to data processing and modeling
Handles prediction and
classification problems
WHAT ABM DOES
© Algolytics. All rights reserved. 11
WHY TO USE ABM?
• Lack of data scientists – addressing gap in your
workforce
• Time for modeling decreased from days to minutes
• Savings - no need to hire a team of data scientists &
analysts. Non-data scientists can learn to quickly
build accurate models using ABM
• Get better insight about your data
© Algolytics. All rights reserved. 12
HOW IT WORKS?
1. Data import 2. Data split 3. Data sampling 4. Exploratory data
analysis
5. Variables
selection
6. Data quality
• Handling of missing values
• Handling of outliers
7. Variables
transformation
8. Variables
interactions
9. Variables
selection
10. Models
building and
selection
11. Reports
generation 12. Data scoring
© Algolytics. All rights reserved. 13
4 steps to calculate prediction
© Algolytics. All rights reserved. 14
4 STEPS TO MAKE PREDICTIONS
• Amazon Elastic Compute
Cloud
• Transferred securely using
SSL protocol
• File format: CSV
Import the source dataset
STEP 1
© Algolytics. All rights reserved. 15
4 STEPS TO MAKE PREDICTIONS
Parameters
• Working Mode (Quick, Advanced, Gold)
• Target variable name and its positive value (numerical, text)
• Variables’ type and role
• Sample selection method and sample size
• Stratified sampling method and proportion of positive target in the resulting sample
• Model quality measure (Lift, Accuracy, Recall, Captured Response)
• Cut off value (Lift, Captured Response)
• Classification Threshold
Run the model building process
STEP 2
© Algolytics. All rights reserved. 16
4 STEPS TO MAKE PREDICTIONS
• 7 reports available • Raw data
• Data split
• Data sampling
• Exploratory data analysis
• Variables selection
• Models statistics (e.g. variables significance, quality measure – statistics and graphs)
• Re-run the process with different settings and test various approaches
Review and understand the model
STEP 3
© Algolytics. All rights reserved. 17
MAKE PREDICTIONS IN 4 STEPS
• Score data, so you can apply the prediction to new data (e.g. score new customers)
• Output file format: .csv • Id variable
• Predicted target value
• The probability of positive value of the target variable
Score data STEP 4
Try out
ABM tool
Visit
www.Algolytics.com click here to open
Questions? Leave a comment or email us
abm_support @ algolytics.com
Visit
www.Algolytics.com click here to open