Download XLMiner Demonstration

XLMiner –
a Data Mining Toolkit
www.xlminer.com
QuantLink Solutions Pvt. Ltd.
www.quantlink.com
XLMiner – a quick tour
Here is a short demo of XLMiner.
Let us use a simple example:
a bank sends mailers to its customers, offering a special
deal on Personal Loans. In its previous campaign, it got
only about 9% positive response.
Objective: How to target customers for increased
conversion rate.
In other words, the question to address is:
what profile indicates a high-potential customer?
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XLMiner – a quick tour
Past campaign data will be used to train the
data mining model
This is called supervised learning in
DataMining terms
Let’s see how to build a model and use it
for improving the response rate.
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XLMiner Quick Tour
Data description
Our past campaign data has the following
customer attributes:
Customer ID
Customer’s Age
Professional Experience
Family Income
Credit Card average annual spending
Education Level
#appliances owned
Did this customer accept past campaign offer?
The last variable is the known outcome of the past campaign. Our
Data Mining model will use this for Supervised Learning.
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XLMiner Quick Tour
A view of the data
This is what the data looks like:
The variable labeled as
“PersLoan?” is binary:
0 means the customer
was not interested in
the Personal Loan.
1 means the customer
was interested.
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XLMiner Quick Tour
the Data Mining Process
Partition the data into
Training & Validation
Partitions
Fit the Model on
Training Partition only
Check if they
are good for
Validation data too!
Try out several
alternative models
Obtain results, see
if they look good
enough
Study the outputs
for validation data
Choose and deploy
the best model
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XLMiner Quick Tour
Start the analysis
Let’s get going with XLMiner.
Notice that XLMiner is as easy to use as Excel!
All we need to do is use the friendly menus. We follow just
three simple steps to fit a model and see the outputs!
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XLMiner Quick Tour
Step 1: Partition the data
We’ll create two
partitions by choosing
the records randomly.
The Training Partition
will be used for fitting
the model.
The Validation
partition will be used
for checking if the
model gives a good fit
for another piece of
known data.
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XLMiner Quick Tour
Partitioned Data
XLMiner creates a
Partition Sheet
that shows the
data split into Two
partitions.
Easy Hyperlinks on the
Navigator facilitate
viewing of either partition
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XLMiner Quick Tour
Step 2: Fitting the Model
This is a
“Classification”
Problem where we
want to predict
customers as likely /
not likely to take a
Personal Loan.
Let’s use one of the
available techniques –
Classification Tree.
We select input
(predictor) variables
here…
…and the outcome
variable here
Later we can use
other Classification
techniques.
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XLMiner Quick Tour
Step 2: Fitting the Model
The model fit guides us through easy
wizard-like steps.
In these steps we choose techniquespecific parameters and the output
options.
In the end, we click Finish to produce
the results.
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XLMiner Quick Tour
Step 3: Understanding the Outputs
The friendly Output Navigator lets us go over all the outputs.
The Summaries show us the
classification error
percentages – i.e. how well
the model is predicting
Other outputs (like the Tree
here) will tell us the decision
rules that the model is
suggesting.
XLMiner - the Data Mining Toolkit
Many other diagnostic
outputs are available
depending on options we
choose.
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XLMiner Quick Tour
Output 1: Validation Summary
First, we look at how well the model predicted for the
Validation data set
In the Training data where we
already knew the outcome,
156 “will buy” were predicted
correctly, and 38 wrongly.
1801 “Won’t buy” were predicted
correctly and merely 5 wrongly.
Here are the corresponding
error percentages.
The errors are not very small
but could still indicate a
workable model.
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XLMiner Quick Tour
Output 2: the decision rule
Here is the Classification Tree that gives the easy-tounderstand and implement Decision Rules
Cut-off points for different
variables decide whether
to go Left or Right
0: not likely to buy
1: likely to buy
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XLMiner Quick Tour
the decision rule in table form
The same decision rule as shown visually, can be
converted into the table below. This is useful for
implementing it in your information systems.
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XLMiner Quick Tour
Output 3: more details
Each technique (Classification Tree in this case) has additional
helpful outputs
The example here shows the “Prune Log” – how the percentage
error reduced by “pruning” the tree
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XLMiner Quick Tour
Output 4: the Lift Chart
“Lift” tells us how much better the model did compared to a
random targeting of customers. This is one of the most
important outputs.
With our Tree model, we get a much superior
result. In less than 500 mailers sent to high
probability customers, we would get nearly
170 successes!
If customers were targeted
randomly, we would expect this
outcome. For instance, 1000
mailers would probably yield less
than 100 customers.
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XLMiner Quick Tour
Output 5: the Detailed report
The Validation data is “scored” in detail as shown below.
Scoring means using the fitted model to classify each record
of the data.
Probability of success is
computed for each record.
This is what helps XLMiner
suggest selective records
(customers) to target.
Predicted values
can be seen
against the actuals
here.
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XLMiner Quick Tour
Try several techniques!
That was just one of the many techniques in
XLMiner – Classification Tree.
A typical Data Mining exercise involves several
alternative approaches on the same data. This can
be either with different techniques, or with different
parameters, or both.
Comparing multiple approaches lets us “assess”
which model to finally choose for implementation.
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XLMiner Quick Tour
Rich repertoire of techniques!
XLMiner supports a comprehensive array of
supervised learning procedures:
Multiple Linear Regression
Logistic Regression
Classification & Regression Trees
Neural Networks
k Nearest Neighbors
Naïve Bayes Classifier
Discriminant Analysis
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XLMiner Quick Tour
Rich repertoire of techniques!
... and several other features in Unsupervised
Learning, Data Reduction and Exploration:
Principal Components Analysis
k-means Clustering
Hierarchical Clustering
Self-organizing Maps (coming soon)
Affinity– Market Basket Analysis
Here are some sample outputs from
these methods …
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XLMiner Quick Tour
sample output - Dendrogram
Hierarchical Clustering produces a dendrogram – an
excellent visual representation of Cluster formation.
Height of the bars is a measure of
dissimilarity in the clusters that are
merging into one.
Smaller clusters “agglomerate” into
bigger ones, with least possible loss of
cohesiveness at each stage.
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XLMiner Quick Tour
sample output – cluster predictions
Cluster Analysis has many powerful uses like Market
Segmentation. We can view individual record’s
predicted cluster membership.
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XLMiner Quick Tour
sample output – BoxPlots
XLMiner supports powerful visualization. The example
here shows BoxPlots of two variables.
Cluster 2 clearly shows higher
Income & Credit Card spend
than Cluster 1. This is an
excellent aid to characterizing
the clusters
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XLMiner Quick Tour
sample output – Scatter Plots
Matrix Scatterplots in XLMiner give a visual insight into
relationship among variables.
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XLMiner Quick Tour
sample output – Association Rules
For Market Basket Analysis XLMiner produces
easy-to-read Association Rules
Rules are explained in
simple English!
Each rule tells us which
offerings will go well together
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XLMiner Quick Tour
… and that’s not all!
XLMiner has handy utilities for Data
handling:
Missing data treatment
Transforming categorical data
Binning continuous data
Sampling from Databases
Scoring to Databases
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XLMiner Quick Tour
XLMiner => Versatility!
This was a quick demonstration of just a few
things XLMiner can do.
It can do lots more. It is comprehensive in
coverage, like the best DM products around.
Get your free download for evaluation at
www.xlminer.ncom
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XLMiner Quick Tour
XLMiner => Simplicity!
Daryl Pregibon had said – Data Mining is
“Statistics at Scale and Speed”.
You’ll find that XLMiner is Statistics at Scale,
Speed and Simplicity!
If you know to use Excel, you already know
XLMiner. You can get started in minutes.
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XLMiner Quick Tour
XLMiner => Great Value!
Several comprehensive DM products are
many times more expensive.
For exploring how Data Mining will work
for you, XLMiner provides a great start!
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XLMiner Quick Tour
What others say …
The American Statistician reviewed XLMiner along with
other reputed products in the November 2003 issue
This is what it had to say:
“An easy to use… an excellent, inexpensive add-on that
greatly expands the capabilities of Excel.”
“XLMiner’s documentation is remarkably good…”
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XLMiner Quick Tour
More Resources
For your initiation into Data Mining:
Free evaluation download
Online Courses at www.statistics.com
Case Book in the making
Technical references on product
website
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XLMiner Quick Tour
Thank you for viewing this Demo!
XLMiner - the Data Mining Toolset
for the Managers of Tomorrow
www.xlminer.com
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