Diabetes Type 2: Poincar�Data Preprocessing for Quantum Machine Learning
نویسندگان
چکیده
منابع مشابه
Global discretization of continuous attributes as preprocessing for machine learning
Real-life data usually are presented in databases by real numbers. On the other hand, most inductive learning methods require a small number of attribute values. Thus it is necessary to convert input data sets with continuous attributes into input data sets with discrete attributes. Methods of discretization restricted to single continuous attributes will be called local, while methods that sim...
متن کاملDiscretization of Numerical Attributes Preprocessing for Machine Learning
Page 2 of 46 Abstract The area of Knowledge discovery and Data mining is growing rapidly. A large number of methods is employed to mine knowledge. Several of the methods rely of discrete data. However, most datasets used in real application have attributes with continuously values. To make the data mining techniques useful for such datasets, discretization is performed as a preprocessing step o...
متن کاملPreprocessing Input Data for Machine Learning by FCA
The paper presents an utilization of formal concept analysis in input data preprocessing for machine learning. Two preprocessing methods are presented. The first one consists in extending the set of attributes describing objects in input data table by new attributes and the second one consists in replacing the attributes by new attributes. In both methods the new attributes are defined by certa...
متن کاملQuantum adiabatic machine learning
We develop an approach to machine learning and anomaly detection via quantum adiabatic evolution. In the training phase we identify an optimal set of weak classifiers, to form a single strong classifier. In the testing phase we adiabatically evolve one or more strong classifiers on a superposition of inputs in order to find certain anomalous elements in the classification space. Both the traini...
متن کاملQuantum-enhanced machine learning
The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computers, Materials & Continua
سال: 2021
ISSN: 1546-2226
DOI: 10.32604/cmc.2021.013196