WIND ENERGY PRODUCTION PROJECT – presentation – Nowadays, we are working to solve a short term prediction problem to solve the biggest wind farm production problem – Energy – RENEWABLE ENERGIES PROJECT: Wind Farm Predictions 1. AN IDEA WAS BORN The idea was born based on the need to optimize the scheduling of daily energy to maintain… Read More »Energy Services (PROJECT)
Data mining Tools
What is the difference between supervised and unsupervised learning algorithms? I’ve heard this question a lot of times. This post is exclusively dedicated to extensively explain the difference between supervised and unsupervised learning algorithms. The difference between Supervised and Unsupervised Learning In supervised learning, the output datasets are provided (and used to train the model – or machine -) to get the… Read More »Supervised and Unsupervised Learning
Determining which predictors should be included in a model is becoming one of the most critical questions as data are becoming increasingly high-dimensional. For example: • In business, companies are now more proficient at storing and accessing large amounts of information on their customers and products. Large databases are often mined to discover crucial relationships… Read More »How to select the predictors of my model?
Although many of the regression modeling techniques can also be used for classification, the way we evaluate model performance is necessarily very different since metrics like RMSE and R2 are not appropriate in the context of classification. Therefore, I’m going to take an in-depth look at the different aspects of classification model predictions and how these relate… Read More »Classification models
For models predicting a numeric outcome, some measure of accuracy is typically used to evaluate the effectiveness of the model. However, there are different ways to measure accuracy, each with its own nuance. To understand the strengths and weaknesses of a particular model, relying solely on a single metric is problematic. Visualizations of the model… Read More »Regression Models
Many classification and regression models are capable of creating complex relationships (adaptable). However, all of them can very easily overemphasize patterns that are not reproducible (such as you seem to observe a face hidden on a cup of coffee). This is a big problem because the modeler do not know anything about the problem until… Read More »Over-fitting & Model Tuning
These are some of the most important aspects to consider for data preprocessing in data mining before apply the data science methodology. Especially for those who are new to Data Science, you must recognize not only the huge relevance of the data preprocessing step but the following aspects before conducting a data mining study. PRE – Data… Read More »Aspects to consider before Data Preprocessing in Data Mining
The Data Mining methods are well-known by all data scientist. However, for beginners, it seems really interesting to know their different applications in data mining. This post provides a short review of the most important and frequent data mining methods. This short-review only highlights some of their influences with data-problems and some of the main features of these data mining methods, techniques or procedures.… Read More »Data Mining Methods
What is data mining? Sometimes, people distinguish Data Mining as synonym of the process of discover knowledge in data (Knowledge Discovery in Databases process). Others, Data Mining (DM) is seen as the main step of Knowledge Discovery in Databases (KDD). I prefer to lead the answer to the data mining process definition (or also known… Read More »Data Mining Process – What is data mining?
The predictive modeling science has evolved throughout a huge number of fields such as physics, chemistry, computer science and statistics. In most cases, Predictive Modeling is called “machine learning” or “artificial intelligence” to make this study-field looks more interesting. However, predictive modeling is not more than the art of creating a “pattern recognition” (predictive analytics)… Read More »Predictive Modeling