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  • Data Mining Algorithms – Logistic Regression

    It’s been awhile since I wrote the last blog on the data mining / machine learning algorithms. I described the Neural Network algorithm. In addition, it is a good time to write another post in order to remind the readers of the two upcoming seminars about the algorithms I have in Oslo, Friday, September 2nd, 2016, and in Cambridge, Thursday, ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on August 31, 2016
  • DevWeek 2016 BI in SQL Server 2016 Workshop Setup

    I got some questions about virtual machine / notebook setup for my Business Intelligence in SQL Server 2016 DevWeek post-conference workshop. I am writing this blog because I want to spread this information as quickly as possible. There will be no labs during the seminar, no time for this. However, I will make all of the code available. ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on April 15, 2016
  • Data Integration is the Foundation

    Unless you live under a rock, you’ve seen the buzz about Data Lakes, Big Data, Data Mining, Cloud-tech, and Machine Learning. I watch and read reports from two perspectives: technical and as a consultant. As a Consultant If you watch CNBC, you won’t hear discussions about ETL Incremental Load or Slowly Changing Dimensions Design Patterns. You ...
    Posted to Andy Leonard (Weblog) by andyleonard on January 29, 2016
  • Data Mining Algorithms – Neural Network

    A neural network is a powerful data modeling tool that is able to capture and represent complex input/output relationships. The motivation for the development of neural network technology stemmed from the desire to develop an artificial system that could perform "intelligent" tasks similar to those performed by the human brain. Neural ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on January 26, 2016
  • Data Mining Algorithms – Decision Trees

    Decision Trees is a directed technique. Your target variable is the one that holds information about a particular decision, divided into a few discrete and broad categories (yes / no; liked / partially liked / disliked, etc.). You are trying to explain this decision using other gleaned information saved in other variables (demographic data, ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on October 29, 2015
  • Data Mining Algorithms – Naive Bayes

    I am continuing with my data mining and machine learning algorithms series. Naive Bayes is a nice algorithm for classification and prediction. It calculates probabilities for each possible state of the input attribute, given each state of the predictable attribute, which can later be used to predict an outcome of the predicted attribute based on ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on September 9, 2015
  • Data Mining Algorithms – Support Vector Machines

    Support vector machines are both, unsupervised and supervised learning models for classification and regression analysis (supervised) and for anomaly detection (unsupervised). Given a set of training examples, each marked as belonging to one of categories, an SVM training algorithm builds a model that assigns new examples into one category. An SVM ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on June 23, 2015
  • Data Mining Algorithms – Principal Component Analysis

    Principal component analysis (PCA) is a technique used to emphasize the majority of the variation and bring out strong patterns in a dataset. It is often used to make data easy to explore and visualize. It is closely connected to eigenvectors and eigenvalues. A short definition of the algorithm: PCA uses an orthogonal transformation to convert ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on June 2, 2015
  • Data Mining Algorithms – K-Means Clustering

    Hierarchical clustering could be very useful because it is easy to see the optimal number of clusters in a dendrogram and because the dendrogram visualizes the clusters and the process of building of that clusters. However, hierarchical methods don’t scale well. Just imagine how cluttered a dendrogram would be if 10,000 cases would be shown on ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on April 17, 2015
  • Data Mining Algorithms – Hierarchical Clustering

    Clustering is the process of grouping the data into classes or clusters so that objects within a cluster have high similarity in comparison to one another, but are very dissimilar to objects in other clusters. Dissimilarities are assessed based on the attribute values describing the objects. There are a large number of clustering algorithms. The ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on March 28, 2015
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