[PDF] Top 20 Machine learning for geological mapping : algorithms and applications

... attractive algorithms for classifying high-dimensional input variables as they offer in-built methods for the selection of important variables and/or mechanisms that control how the algorithm learns to focus on ... See full document

... Abstract— Machine Learning (ML) furnishes the ability of insights on automatic recognizing patterns and determining the prediction models for the structured and unstructured data even in the absence of ... See full document

... Machine learning research spans almost four ...of learning, establishing the relationship among them, and elaborate the algorithms that characterize ...bring machine learning to ... See full document

... ABSTRACT: Machine learning is a field of computer science which gives computers an ability to learn without being explicitly ...programmed. Machine learning is used in a variety of ... See full document

... VariousML algorithms have been introduced and experimented on in a number of ...ML algorithms, and appropriate case or scenarios to use a particular ...classification algorithms, Naive Bayes and ... See full document

... DTN. Machine Learning approaches[26] can be applied to adapt to network changes, efficiently route the packets, reduce overhead, congestion ...control. Machine Learning approaches are accurate ... See full document

... of learning is preferably used in robotics and automation, gaming world, for navigation purpose and various other ...dynamic learning approach that creates an environment to achieve a definite outcome ... See full document

... different machine learning algorithms for classification such as J48, JRip, SMO, Naïve Bayes and ...uses machine learning algorithms to detect malicious ...classifier ... See full document

... systems machine learning algorithms are used to perform security-related applications like biometric authentication, network intrusion detection, and spam filtering, to distinguish between a ... See full document

... The geological mapping in tropical areas with dense rain forest vegetation and thick supergene covers is challenging as rock exposure is very poor, and access to outcrops can be ...of geological ... See full document

... of machine learning system came into lime ...Modern Machine Learning is highly accurate predictions on test ...several applications of Machine Learning; the main of all is ... See full document

... are Machine Learning (ML) Approaches. In this paper a machine learning approach is used to distinguish between normal and abnormal ...processing algorithms can improve processing speed ... See full document

... VECTOR MACHINE : In machine learning, support vector machines are supervised learning models with associated learning algorithms that analyze data used for classification and ... See full document

... on machine learning algorithms are commonly used in security-related applications like biometric authentication, network intrusion detection, and spam filtering, to discriminate between a ... See full document

... in applications using variables that have mutual nonlinear ...of learning a function that dependent variable (target) X 0 and independent Ifs data X 1 , X 2 ... See full document

... The results of this study proved that Meta classifiers were improved the goodness-of-fit and prediction accuracy of ADTree as a single-based algorithm (base classifier) in the two scenarios. Our findings were reasonable ... See full document

... Ineffective conditioning factors creates noise and decreases the prediction capability of modelling using training dataset [59]. The results of selecting the most significant conditioning factors affecting land ... See full document

... The all-weather capability of microwave active sensing makes Synthetic Aperture Radar (SAR) a useful tool for rice crop mapping. SAR observations at different points during the rice crop growing season are ... See full document

... reinforcement learning (IRL) infers a reward function from demonstrations, allowing for policy improvement and ...a machine teaching problem where the goal is to find the minimum number of demonstrations ... See full document

... on machine learning algorithm, virtual ma- chine classification algorithm (K-Means-OMM), and multi-objective optimization algorithm (ESA_DE) based on ...MAD_RS algorithms, the migration cost, network ... See full document