Predictive modeling is a statistical technique used to predict the outcome of future events based on historical data. It involves building a mathematical model that takes relevant input variables and generates a
Surface modeling is a CAD (computer-aided design) technique used to create and manipulate the external surfaces of a 3D object. Unlike solid modeling, which defines both the interior and exterior of an object, surface modeling focuses solely on the outer shell, allowing designers to create ...
UML is a notation that resulted from the unification of OMT from Object Modeling Technique OMT[James Rumbaugh1991] - was best for analysis and data-intensive information systems. Booch [Grady Booch1994] - was excellent for design and implementation. Grady Booch had worked extensively with theAdala...
Clustering:Clustering is an unsupervised learning technique that groups data points according to their properties or similarities. The primary objective here is to recognize the relationship and similarity between given data points, and based on that, we need to group them into separate clusters, conta...
This paper attempts to demystify the technique of causal path modeling for the non-specialists by presenting aspects of its value for social science and management research and by illustrating common misunderstandings about its attributes. Special emphasis is placed on the real world validity of causal...
Machine learningis a critical technique that enables AI to solve problems. Despite common misperceptions (and misnomers in popular culture), machines do not learn. They store and compute — admittedly in increasingly complex ways. Machine learning solves business problems by using statistical models to...
is a visual representation of data modeling using symbols and notation that describes how these data are related to each other. It can directly be used by database developers as the blueprint for implementing data in specific software applications. Any object, such as entities, attributes of an...
Anomaly detection is the process of identifying outliers or unusual data points that deviate significantly from the rest of the dataset. This technique is critical for spotting potential errors, fraud, or unusual trends that could indicate important changes in the data. It functions as a tool for...
Object-oriented data modeling Asobject-oriented programmingadvanced in the 1990s and software vendors developed object databases, object-oriented data modeling also emerged. The object-oriented approach is similar to the ER method in how it represents data, attributes and relationships, but it abstracts...
What is the difference between AI and ML? Artificial intelligence (AI) is a broad field that refers to the ability of a machine to complete tasks that typically require human intelligence. Machine learning (ML) is a subfield of artificial intelligence that specifically refers to machines that can...