Frequent item set mining and association rule induction [Agrawal et al. 1993, 1994] are powerful methods for so-called market basket analysis, which aims at finding regularities in the shopping behavior of customers of supermarkets, mail-order companies, online shops etc. With the induction of frequent item sets and association rules one tries to find sets of products that are frequently bought together, so that from the presence of certain products in a shopping cart one can infer (with a high probability) that certain other products are present. Such information, especially if expressed in the form of rules, can often be used to increase the number of items sold, for instance, by appropriately arranging the products on the shelves of a supermarket or on the pages of a mail-order catalog (they may, for example, be placed adjacent to each other in order to invite even more customers to buy them together) or by directly suggesting items to a customer, which may be of interest for him/her.
An association rule is a rule like "If a customer buys wine and bread, he/she often buys cheese, too." It expresses an association between (sets of) items, which may be products of a supermarket or a mail-order company, special equipment options of a car, optional services offered by telecommunication companies etc. An association rule states that if we pick a customer at random and find out that he/she selected certain items (bought certain products, chose certain options etc.), we can be confident, quantified by a percentage, that he/she also selected certain other items (bought certain other products, chose certain other options etc.).
A full description of the algorithm (included in the source package) is available on Christian Borgelts web page. The additional parameters described on this page can be applied via the additional parameter field of the "Advanced Settings" tab.
(*) RULE LEARNER is a registered trademark of Minitab, LLC and is used with Minitab’s permission.
Options
Advanced Settings
Popular Predecessors
Cell Splitter27 %- Double Configuration8 %
- Cell Splitter6 %
CSV Reader4 %Double Input (legacy)3 %Excel Reader (XLS)3 %- Create Collection Column2 %
Number To String2 %- Number to String2 %
- GroupBy2 %
Table Reader1 %- Rule Engine1 %
- Partitioning1 %
- Math Formula1 %
Joiner< 1 %Column Rename< 1 %- Table View (JavaScript)< 1 %
- Table Creator< 1 %
- Create Bit Vector< 1 %
- Excel Reader< 1 %
- Set Operator< 1 %
- String Manipulation< 1 %
- Reference Row Splitter< 1 %
- Integer Input (legacy)< 1 %
- Parameter Optimization Loop Start< 1 %
- One to Many< 1 %
- Pivot< 1 %
- Association Rule Learner< 1 %
String To Number< 1 %Row Filter (deprecated)< 1 %- Missing Value< 1 %
- Column Splitter< 1 %
- Parallel Chunk Start< 1 %
- File Reader< 1 %
- Column Filter< 1 %
- Value Counter< 1 %
- Split Collection Column< 1 %
- Date&Time-based Row Filter< 1 %
- String to Number< 1 %
- Double Widget< 1 %
- Row Aggregator< 1 %
- Java Snippet< 1 %
- Concatenate< 1 %
- Column Combiner< 1 %
- Column Aggregator< 1 %
- Filter Apply< 1 %
- RowID< 1 %
- Sorter< 1 %
- Table Transposer< 1 %
- Association Rule Learner (Borgelt)< 1 %
- Item Set Finder (Borgelt)< 1 %
- Double Input (legacy)< 1 %
- Duplicate Row Filter< 1 %
- Ungroup< 1 %
- CSV Reader< 1 %
- Table Reader< 1 %
- Joiner< 1 %
- One Rule Inserter< 1 %
- Column Expressions (legacy)< 1 %
- ARFF Reader< 1 %
Database Connection Table Reader< 1 %Line Reader< 1 %- Group Loop Start< 1 %
- Column to Grid< 1 %
Linear Correlation< 1 %- Nominal Value Row Filter< 1 %
Row Splitter (deprecated)< 1 %- Ruleset Predictor< 1 %
Column Selection QuickForm (legacy)< 1 %- Try (Variable Ports)< 1 %
- Auto-Binner< 1 %
- Row Filter (Labs)< 1 %
XLS Reader< 1 %Table Row to Variable< 1 %Table Row To Variable Loop Start< 1 %Loop End< 1 %Scorer< 1 %- Reference Row Filter< 1 %
- Color Manager< 1 %
Database Reader< 1 %Concatenate (Optional in)< 1 %- Expand Bit Vector< 1 %
- Category to Number< 1 %
- Statistics< 1 %
Excel Reader (XLS)< 1 %- Category to Class< 1 %
- Slider Input (legacy)< 1 %
XML Reader< 1 %- Document Vector< 1 %
- URI to String< 1 %
File Reader< 1 %Interval Loop Start< 1 %- Chunk Loop Start< 1 %
- Reference Column Filter< 1 %
- Normalizer< 1 %
- Row Sampling< 1 %
- Rule-based Row Filter< 1 %
- Rule-based Row Splitter< 1 %
- Boosting Learner Loop Start< 1 %
- Math Formula (Multi Column)< 1 %
Excel Reader (XLS)< 1 %Document vector< 1 %- Combine Columns by Header< 1 %
- Strings to Binary Objects< 1 %
- Loop End (Column Append)< 1 %
- PNN Predictor< 1 %
- Random Forest Learner< 1 %
- Numeric Binner< 1 %
- Create Byte Vector< 1 %
- Cell Splitter By Position< 1 %
- Column Comparator< 1 %
- Number to Category (Apply)< 1 %
- Column Renamer (Dictionary)< 1 %
- Column Merger< 1 %
- Column Resorter< 1 %
- CAIM Binner< 1 %
- Subset Matcher< 1 %
- Numeric Binner (PMML)< 1 %
Number To String (PMML)< 1 %- Unpivot< 1 %
Rank Correlation< 1 %- IF Switch< 1 %
- Data Generator< 1 %
- DB Reader< 1 %
- Counter Generation< 1 %
- Random Item Inserter< 1 %
- Math Formula (Variable)< 1 %
Read Excel Sheet Names (XLS)< 1 %- Date&Time Input (legacy)< 1 %
Extract Date&Time Fields< 1 %- Time Generator (legacy)< 1 %
- List To Set< 1 %
Counting Loop Start< 1 %- Bootstrap Sampling< 1 %
- Column Appender< 1 %
- Constant Value Column< 1 %
- Table Validator< 1 %
- Double to Integer< 1 %
- Interactive HiLite Collector< 1 %
- Integer Slider Configuration< 1 %
- File Upload (legacy)< 1 %
- String Input (legacy)< 1 %
- Python Edit Variable (legacy)< 1 %
Views
- This node has no views
Workflows
01_Build_Association_Rules_for_MarketBasketAnalysisKNIME Hub- 01_Build_Association_Rules_for_MarketBasketAnalysisKNIME Hub
- 01_Build_Association_Rules_for_MarketBasketAnalysisKNIME Hub
- 01_Build_Association_Rules_for_MarketBasketAnalysisKNIME Hub
- 01_Build_Association_Rules_for_MarketBasketAnalysisKNIME Hub
- Show all 115 workflows
Links
Developers
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.