These algorithms make use of conditional probability through their support, confidence and lift , showing whether a product or products are purchased together with one or more other products with a higher probability than would be expected.
Others there are many additional applications where data mining can be applied.
Sometimes, we simply want to reduce the dimensionality of the input variables to estimate, classify or segment a target variable by studying the variability or information gain that these input variables offer.
At the numerical level we can name the anova and pca algorithms
Other times, we can use algorithms with higher performance and a high volume of input variables and records.
In this case, we can use neural networks ( deep learning ) to classify or establish a regression.
We can also use convolutional networks belgium phone number list for handwritten text classification and image interpretation, human language interpretation or nlp.
The field of neural networks offers a leap into a more complex field of application.
There are applications where we would like
to classify texts based on a topic in order to favor search engines or open new sectors.
Using text mining, you can learn the frequency it must be feasible to achieve the objectives of certain words based on their subject matter and classify text based on its content .
Conclusion
data mining offers a qualitative leap for any organization seeking to increase its competitive capacity.
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as we have described in previous sections, having spam data quality resources and the governance to generate them requires comprehensive organizational changes.
Mastering data mining allows you to gain knowledge and facilitate decision-making in a faster and more accurate way.