Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 12 of 12 for “"decision tree classifier"”.
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Urban land cover mapping using medium spatial resolution satellite imageries: effectiveness of Decision Tree Classifier
… spatial resolution Landsat data processing; Decision Tree classifier was investigated as classification techniques, thus it allows to extract rules that can be later applied to different scenes. In particular, the aim was to evaluate which steps to perform in order to obtain a good …
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Binary tree classifier and context classifier
Two methods of designing a point classifier are discussed in this paper, one is a binary decision tree classifier based on the Fisher's linear discriminant function as a decision rule at each nonterminal node, and the other is a contextual classifier which gives each pixel the highest probability …
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Power Efficient Wireless Sensor Node through Edge Intelligence
… sensor node with a LoRa radio and implemented a decision tree classifier, in situ, to classify behaviors of cattle. We estimate that employing edge intelligence on our wireless sensor node reduces its average power dissipation by up to a factor of 50, from 20.10 mW to 0.41 mW. We also observe …
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An automated framework for power-efficient detection in embedded sensor systems
… sensor systems. The core of this framework is a decision tree classifier that dynamically orders the activation and adjusts the sampling rate of the sensors, such that only the data necessary to determine the system state is collected at any given time.
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Blind recognition of analog modulation schemes for software defined radio
… In this dissertation, a Cyclostationarity-Based Decision Tree classifier is developed to separate between analog modulations and digital modulations, and classify signals into several subsets of modulation types. In order to further recognize the specific modulation type of analog signals, more …
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Localized methods for protein interaction prediction
… maps to guide and constrain alignments. Using a decision tree classifier and low-throughput experimental data for training, it combines information inferred from statistical interaction potentials, energy functions, correlated mutations and conserved residue pairs to predict likely interactions. …
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An improved framework for content and link-based web spam detection: a combined approach
… has been evaluated and compared with the J48 classifier, C4.5 decision tree classifier, SVM classifier, and heuristic combined approach. Some experiments were conducted to obtain the threshold values using the proposed collection architecture on well-known datasets WEB SPAM-UK2006 and WEB …
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Task Analysis, Modeling, And Automatic Identification Of Elemental Tasks In Robot-Assisted Laparoscopic Surgery
… based on surgeon hand gestures. An automatic classifier was trained on the subtasks identified during the Hierarchical Task Analysis of a four-throw suturing task and the motion signature recorded during task performance. Using principal component analysis and a J48 decision tree classifier, …
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DDoS defence for service availability in cloud computing
… methods to achieve an optimum selection, and a decision-tree classifier to detect DDoS attacks; and (iii) this thesis proposes a change-point monitoring algorithm to detect DDoS flooding attacks against cloud services, by examining the packet IAT. A DDoS attack pattern is distinguished from …
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Machine and Deep Learning Approach for Type 2 Diabetes Prediction Using the CDC’s BRFSS Dataset: A Retrospective Analysis
… (ML) and neural network or multilayer perceptron classifier (NN) model(s) and test their performance on predicting the risk for T2DM. A copy of the dataset was transformed to have balanced classes in the outcome variable to allow further comparison of performance for each predictive model when …
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High-Latitude Ionospheric Irregularities Characterized Through Machine Learning Methods
… the auroral oval vs. one from the polar cap, a decision tree model was trained to classify the signatures. For hours in which both stations were located in their characteristic regions as confirmed by electron energy flux observations, the model achieved a good performance, whereas in hours with …
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Flood risk assessment using multi-sensor remote sensing, geographic information system, 2D hydraulic and machine learning based models
… satellite images. Dempster–Shafer (DS) fusion classifier was proposed in this part as a feature-based image analysis (FBIA) to extract urban complex objects. The DS-FBIA was investigated among two sites to examine the transferability of the proposed method. In addition, the DS-FBIA was compared …