How to determine the quality and correctness of classification models? Part 2 – Quantitative quality indicators

In this part of tutorial we will discuss derived quality indicators and show how to select the appropriate indicator using as an example churn analysis.

Learn more
Quality and correctness of classification models

Tutorial: How to determine the quality and correctness of classification models? Part 1 – Introduction

What is classification?

Classification is the process of assigning every object from a collection to exactly one class from a known set of classes.

Learn more
Data Quality Projects

What is data quality all about and how to run a data cleaning project?

Are you considering carrying out or outsourcing a data cleaning project? Find out what our experience tells us about this types of analyses.

Learn more

Understanding machine learning #3: Confusion matrix – not all errors are equal

One of the most typical tasks in machine learning is classification tasks. It may seem that evaluating the effectiveness of such a model is easy. Let’s assume that we have a model which, based on historical data, calculates if a client will pay back credit obligations. 

Learn more
Machine learning

Understanding machine learning #2: Do we need machine learning at all?

In the previous post of our Understanding machine learning series, we presented how machines learn through multiple experiences. We also explained how, in some cases, human beings are much better at interpreting data than machines. 

Learn more
Machine Learning

Understanding Machine Learning #1 – How machines learn?

“If (there) was one thing all people took for granted, (it) was conviction that if you feed honest figures into a computer, honest figures (will) come out. Never doubted it myself till I met a computer with a sense of humor.” ― Robert A. Heinlein, The Moon is a Harsh Mistress

Learn more
Data mart

Analytical Data Marts – data analysts’ indispensable tool

Information about provided services, customers and transactions can be stored in different database systems and data warehouses, depending on the way in which a company operates.

Due to such arrangements, even the simplest analyses or report may require significant expenditures of time, as well as in-depth knowledge about database systems and their availability.

Learn more

Correlation does not imply causation

A popular phrase tossed around when we talk about statistical data is “there is correlation between variables”. However, many people wrongly consider this to be the equivalent of “there is causation between variables”. It’s important to explain the distinction:

Learn more

Predictive Analytics glossary

As Predictive Analytics (also called Data Mining or Data Science) is gaining momentum and spreading across companies and sectors, we have created a short guide to some common terms in this field. We hope you like it!

Learn more

Customer data analysis – part 2

In the previous post we presented a few methods of data analysis, which are used to identify customer needs and preferences and allow us to predict their behavior. Such knowledge results in building better marketing and sales offers which meet specific customer expectations. In today's article we present further examples of Data Mining methods that can be applied in daily business operations.


Learn more
Customer data analysis – part 1

Customer behavior data analysis – part 1

The key asset of any company is its customers. Therefore, it is crucial to identify their needs and preferences as well as to know the factors affecting their behavior. The collected customer data allows predicting customer behavior and creating appropriate marketing offers, sales plans, and retention programs that match customers' needs.

Learn more

Algoline platform hailed as Polish Innovation in Big Data!

On April 20, in the BIG Data Awards Gala, we received a prize in the BIG DATA Congress: Think Big CEE competition for Polish Innovation. The award in this category is given to outstanding Polish companies for introducing groundbreaking technologies and for having real impact on the shaping of the market.

Learn more