National Repository of Grey Literature 10 records found  Search took 0.00 seconds. 
Overview of Actual Approaches to Classifications
Brezánský, Tomáš ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks, Bayesian classifiers and decision trees. The main task of this work is to perform experiments with three classification algorithms, namely, the ID3 algorithm, the RCE neural network and the naive Bayesian classifier. The work contains experiments with given algorithms and evaluates the obtained results.
Data Mining with Python
Krestianková, Tamara ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with principles of data mining process, available Python packages for data mining and a demonstration of Python script capable of data analyisis focused on classification techniques. Created classifiers are able to classify subjects into two groups - healthy people and people suffering from Parkinson's disease - based on their biomedical vocal analysis data.
Overview of Actual Approaches to Classifications
Brezánský, Tomáš ; Šůstek, Martin (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks, Bayesian classifiers and decision trees. The main task of this work is to perform experiments with three classification algorithms, namely, the ID3 algorithm, the RCE neural network and the naive Bayesian classifier. The work contains experiments with given algorithms and evaluates the obtained results.
Smart Sensor Network with Using Mobile Devices
Tomčík, Milan ; Zbořil, František (referee) ; Samek, Jan (advisor)
This bachelor thesis deals with the use of mobile devices as sensors of various activities. Different types of mobile device sensors are used, in particular the gyroscope, accelerometer and magnetometer. The thesis tackles the possibility of utilization of mobile devices as part of the nodes in a sensor network, while employing mobile device and fusing data obtained from their sensors.
Fundamental Analysis for Automatic Trading Systems
Miček, Marek ; Kanich, Ondřej (referee) ; Rozman, Jaroslav (advisor)
This thesis deals with the creation of automatic trading systems which are able to predict market trends for stocks selected in advance. Proper trading strategy of this system is mainly created from the elements of fundamental analysis, such as annual returns of company, it's gains, level of shareholder's equity or total debt. All the stocks are classified by these fundaments, where result of this classification determines whether to buy or sell the stock. For the purpose of this thesis, 5 autamatic trading systems were created in order to compare different approaches to the stock evaluation, managment or diversification of business portfolio. Created systems were properly tested on historical data and, in order to determine their level of complexity, tests were executed in both periods of economic recession and expansion too. All the created systems reported great returns and most of them have potential to generate long-term gains. On the basis of received results, it is possible to make conclusion that fundamental analysis has a high value in the field of automatic trading systems, and it increases the chances of generating a profit.
Fundamental Analysis for Automatic Trading Systems
Miček, Marek ; Kanich, Ondřej (referee) ; Rozman, Jaroslav (advisor)
This thesis deals with the creation of automatic trading systems which are able to predict market trends for stocks selected in advance. Proper trading strategy of this system is mainly created from the elements of fundamental analysis, such as annual returns of company, it's gains, level of shareholder's equity or total debt. All the stocks are classified by these fundaments, where result of this classification determines whether to buy or sell the stock. For the purpose of this thesis, 5 autamatic trading systems were created in order to compare different approaches to the stock evaluation, managment or diversification of business portfolio. Created systems were properly tested on historical data and, in order to determine their level of complexity, tests were executed in both periods of economic recession and expansion too. All the created systems reported great returns and most of them have potential to generate long-term gains. On the basis of received results, it is possible to make conclusion that fundamental analysis has a high value in the field of automatic trading systems, and it increases the chances of generating a profit.
Overview of Actual Approaches to Classifications
Brezánský, Tomáš ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks, Bayesian classifiers and decision trees. The main task of this work is to perform experiments with three classification algorithms, namely, the ID3 algorithm, the RCE neural network and the naive Bayesian classifier. The work contains experiments with given algorithms and evaluates the obtained results.
Overview of Actual Approaches to Classifications
Brezánský, Tomáš ; Šůstek, Martin (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks, Bayesian classifiers and decision trees. The main task of this work is to perform experiments with three classification algorithms, namely, the ID3 algorithm, the RCE neural network and the naive Bayesian classifier. The work contains experiments with given algorithms and evaluates the obtained results.
Data Mining with Python
Krestianková, Tamara ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with principles of data mining process, available Python packages for data mining and a demonstration of Python script capable of data analyisis focused on classification techniques. Created classifiers are able to classify subjects into two groups - healthy people and people suffering from Parkinson's disease - based on their biomedical vocal analysis data.
Smart Sensor Network with Using Mobile Devices
Tomčík, Milan ; Zbořil, František (referee) ; Samek, Jan (advisor)
This bachelor thesis deals with the use of mobile devices as sensors of various activities. Different types of mobile device sensors are used, in particular the gyroscope, accelerometer and magnetometer. The thesis tackles the possibility of utilization of mobile devices as part of the nodes in a sensor network, while employing mobile device and fusing data obtained from their sensors.

Interested in being notified about new results for this query?
Subscribe to the RSS feed.