Once you have the relevant data for analysis, you need to apply appropriate algorithms to determine patterns in the data.
Determining an appropriate algorithm to use for a specific purpose is a challenging task. You can use a combination of a number of algorithms to analyze data. For example, you can first use time series algorithms to smooth data and then use regression algorithms to find trends.
| Purpose | Algorithm |
|---|---|
| Performing time-based predictions | Time Series Algorithms
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| Predicting continuous variables based on other variables in the dataset | Regression Algorithms
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| Finding frequent itemset patterns in large transactional datasets to generate association rules | Association Algorithms
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| Clustering observations into groups of similar itemsets | Clustering Algorithms
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| Classifying and predicting one or more discrete variables based on other variables in the dataset | Decision Trees
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| Detecting outlying values in the dataset | Outlier Detection Algorithms
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| Forecasting, classification, and statistical pattern recognition | Neural Network Algorithms
|