|
|
Comparison of Classification Methods
Dočekal, Martin ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
|
|
|
Using of Data Mining Method for Analysis of Social Networks
Novosad, Andrej ; Očenášek, Pavel (referee) ; Bartík, Vladimír (advisor)
Thesis discusses data mining the social media. It gives an introduction about the topic of data mining and possible mining methods. Thesis also explores social media and social networks, what are they able to offer and what problems do they bring. Three different APIs of three social networking sites are examined with their opportunities they provide for data mining. Techniques of text mining and document classification are explored. An implementation of a web application that mines data from social site Twitter using the algorithm SVM is being described. Implemented application is classifying tweets based on their text where classes represent tweets' continents of origin. Several experiments executed both in RapidMiner software and in implemented web application are then proposed and their results examined.
|
|
|
Room Occupancy Detection with IoT Sensors
Kolarčík, Tomáš ; Jeřábek, Kamil (referee) ; Pluskal, Jan (advisor)
The aim of this work was to create a module for home automation tools Home Assistant. The module is able to determine which room is inhabited and estimate more accurate position of people inside the room. Known GPS location cannot be used for this purpose because it is inaccurate inside buildings and therefore one of the indoor location techniques needs to be used. Solution based on Bluetooth Low Energy wireless technology was chosen. The localization technique is the fingerprinting method, which is based on estimating the position according to the signal strength at any point in space, which are compared with a database of these points using machine learning. The system can be supplemented with motion sensors that ensure a quick response when entering the room. This system can be deployed within a house, apartment or small to medium-sized company to determine the position of people in the building and can serve as a very powerful element of home automation.
|
|
|
Utilization of artificial intelligence in technical diagnostics
Konečný, Antonín ; Huzlík, Rostislav (referee) ; Zuth, Daniel (advisor)
The diploma thesis is focused on the use of artificial intelligence methods for evaluating the fault condition of machinery. The evaluated data are from a vibrodiagnostic model for simulation of static and dynamic unbalances. The machine learning methods are applied, specifically supervised learning. The thesis describes the Spyder software environment, its alternatives, and the Python programming language, in which the scripts are written. It contains an overview with a description of the libraries (Scikit-learn, SciPy, Pandas ...) and methods — K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Trees (DT) and Random Forests Classifiers (RF). The results of the classification are visualized in the confusion matrix for each method. The appendix includes written scripts for feature engineering, hyperparameter tuning, evaluation of learning success and classification with visualization of the result.
|
|
| |
|
|
Classification Framework
Koroncziová, Dominika ; Otrusina, Lubomír (referee) ; Kouřil, Jan (advisor)
The goal of this work is the design and implementation of a machine learning software, based on the RapidMiner library. The finished application integrates the most commonly used algorithms and processes implemented in RapidMiner into an easily usable program. The application contains a simple command line interface, as well as a graphic interface to simplify selection of multiple parameters. The program also provides a tool to create standalone programs, that can be used for classification with a pre-trained model. On top of the original requirements the possibility to work with textual data from Wikipedia was also implemented, providing a tool for downloading and preprocessing of the data in order to use them as training input. This text focuses on the specifics of the algorithms and classifiers used and on their features and uses, and describes the design and implementation of the system. As part of this work, several tests were run in order to validate the efficiency and functionality of the program. The test results are included at the end of the thesis.
|
|
|
Evaluation of Image Recognition
Kučerová, Pavla ; Mlích, Jozef (referee) ; Zemčík, Pavel (advisor)
This work deals with pattern recognition methods and possibilities of their evaluation. It involves design and implementation of the method comparing the influence of preprocessing to pattern recognition algorithms. The method was tested and evaluated for linear classification algorithm, k-Nearest Neighbors, AdaBoost and SVM.
|
|
|
Data Analysis of a Company Producing Medical Supplies
Kulhánková, Monika ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This bachelor's thesis deals with the analysis of the company's sales data, specifically the classification of the customer's type according to his sales data. It provides a theoretical introduction to data mining. It describes the classification process and methods for creating classifiers and presents the CRISP-DM model. This thesis describes the provided data sets, from which the relevant attributes are selected. The data are preprocessed and used in the creation and testing of classification models. The result of this thesis is a comparison of the achieved results.
|
|
|
Handwritten text recognition using a sliding window
Ďuriš, Denis ; Povoda, Lukáš (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with optical character recognition. It focuses on recognizing hand-written text. The theoretical introduction describes the methods used for optical character recognition and selected machine learning methods. Subsequently, the work describes two methods for making cutouts of characters, using a sliding window. Cutouts are used in training and testing datasets of machine learning models. The document includes methods to improve the accuracy of character recognition. The accuracy of the models is evaluated in conclusion. Charcters in cutouts are clasified by an automated recognition program.
|
|
|
ECG arrhythmia detection
Šoltés, Tomáš ; Filipenská, Marina (referee) ; Novotná, Petra (advisor)
This bachelor thesis describes commonly present arrhytmias such as premature ventricular complex, bundle branch blocks and their detection using conventional methods and modern methods, utilising neural networks. Practical part includes: Detection of premature ventricular complexes and detection of bundle branch blocks using statistical analysis of QRS complex and their classification with K-nearest neighbors
|
guest ::
