DATA MINING IN FINANCE AND ACCOUNTING: A - delab-auth
... ANOVA. The authors report better results for the NNs and decision trees models for both the human judgment based and the ANOVA feature selection. Finally, the authors propose a hybrid algorithm employing weighted voting of different classifiers. Marginally better performance is reported for the hyb ...
... ANOVA. The authors report better results for the NNs and decision trees models for both the human judgment based and the ANOVA feature selection. Finally, the authors propose a hybrid algorithm employing weighted voting of different classifiers. Marginally better performance is reported for the hyb ...
AI for CRM: A Field Guide to Everything You
... Machine Learning is the core driver of AI, and involves computers learning from data with minimal programming. Essentially, instead of programming rules for a machine, you program the desired outcome and train the machine to achieve the outcome on its own by feeding it data — for example, personaliz ...
... Machine Learning is the core driver of AI, and involves computers learning from data with minimal programming. Essentially, instead of programming rules for a machine, you program the desired outcome and train the machine to achieve the outcome on its own by feeding it data — for example, personaliz ...
Georgetown MRI Reading Center (GMRC)
... In just the last few years manganese has been used as a neuronal tracer/contrast agent for MRI with phase one clinical trials. During 1991-1999, Dr. Fricke worked with the University of Florence on various projects involving multiplatform imaging for the diagnosis of vision disorders due to cerebral ...
... In just the last few years manganese has been used as a neuronal tracer/contrast agent for MRI with phase one clinical trials. During 1991-1999, Dr. Fricke worked with the University of Florence on various projects involving multiplatform imaging for the diagnosis of vision disorders due to cerebral ...
2017 Trends to Watch: Artificial Intelligence - Ovum
... The telecom industry is also ripe for disruption by AI AI can be used for managing telecom networks in several areas. Orchestration: A fully NFV-enabled network will ultimately be controlled by a single NFV orchestrator (NFVO). Accurately predicting network trends could lead to significant improve ...
... The telecom industry is also ripe for disruption by AI AI can be used for managing telecom networks in several areas. Orchestration: A fully NFV-enabled network will ultimately be controlled by a single NFV orchestrator (NFVO). Accurately predicting network trends could lead to significant improve ...
Does Query-Based Diagnostics Work?
... building and probability elicitation. The second approach, usually referred to knowledge-based model construction (KBMC), emphasizes aiding model building by automated generation of decision models from a domain knowledge-base guided by the problem description and observed information (see a special ...
... building and probability elicitation. The second approach, usually referred to knowledge-based model construction (KBMC), emphasizes aiding model building by automated generation of decision models from a domain knowledge-base guided by the problem description and observed information (see a special ...
the full pdf program here - CDAR
... Locally-biased graph algorithms are algorithms that attempt to find local or small-scale structure in a typically large data graph. In some cases, this can be accomplished by adding some sort of locality constraint and calling a traditional graph algorithm; but more interesting are locallybiased gra ...
... Locally-biased graph algorithms are algorithms that attempt to find local or small-scale structure in a typically large data graph. In some cases, this can be accomplished by adding some sort of locality constraint and calling a traditional graph algorithm; but more interesting are locallybiased gra ...
A Genetic-Firefly Hybrid Algorithm to Find the Best Data Location in
... values for each education input pattern and similar patterns. Moreover, the performances of neural networks are related to the choice of the neurons count, architecture of networks and learning algorithms [28, 44]. The perceptron learning rule is supervised learning in which a stimulus, response, in ...
... values for each education input pattern and similar patterns. Moreover, the performances of neural networks are related to the choice of the neurons count, architecture of networks and learning algorithms [28, 44]. The perceptron learning rule is supervised learning in which a stimulus, response, in ...
- The University of Liverpool Repository
... enable users to introduce links between different level nodes and thus compose a graph structure. This method is now much used in browsing data methods such as knowledge retrieval from the data which also called data-mining (Huyet and Paris, 2004). ...
... enable users to introduce links between different level nodes and thus compose a graph structure. This method is now much used in browsing data methods such as knowledge retrieval from the data which also called data-mining (Huyet and Paris, 2004). ...
Data Clustering Using Evidence Accumulation
... data is split into a large number of compact and small clusters; different decompositions are obtained by random initializations of the K-means algorithm. The data organization present in the multiple clusterings is mapped into a coassociation matrix which provides a measure of similarity between pa ...
... data is split into a large number of compact and small clusters; different decompositions are obtained by random initializations of the K-means algorithm. The data organization present in the multiple clusterings is mapped into a coassociation matrix which provides a measure of similarity between pa ...
Use Cases of Pervasive Artificial Intelligence for Smart Cities
... Smart cities are a hot topic, very cross-disciplinary and consequently studied by many authors in various disciplines. Therefore, many definitions have been proposed, some with more emphasis on performance, or governance, or technology... [10]. Nevertheless, it is generally accepted that smart citie ...
... Smart cities are a hot topic, very cross-disciplinary and consequently studied by many authors in various disciplines. Therefore, many definitions have been proposed, some with more emphasis on performance, or governance, or technology... [10]. Nevertheless, it is generally accepted that smart citie ...
Smart Phone Based Data Mining for Human Activity Recognition
... learning approaches, and time taken to build the model. As can be seen in this figure, we examined 2,8,16, 32, 64, 128, 256 and 561(all features), ranked by information gain approach. The total data size for training and testing comprised around 10,000 samples. We used 5 fold cross validation for pa ...
... learning approaches, and time taken to build the model. As can be seen in this figure, we examined 2,8,16, 32, 64, 128, 256 and 561(all features), ranked by information gain approach. The total data size for training and testing comprised around 10,000 samples. We used 5 fold cross validation for pa ...
Prediction of maximum surface settlement caused by earth pressure
... excavation is an important task. During the recent decades, many attempts have been made to investigate the influencing factors affecting the amount of surface settlement. In this study, random forest (RF) is introduced and investigated for the prediction of maximum surface settlement (MSS) caused b ...
... excavation is an important task. During the recent decades, many attempts have been made to investigate the influencing factors affecting the amount of surface settlement. In this study, random forest (RF) is introduced and investigated for the prediction of maximum surface settlement (MSS) caused b ...
Outlier Reduction using Hybrid Approach in Data Mining
... algorithm cannot select variables automatically because k-means treat all variables equally in clustering process it result in poor clustering. New k-means type clustering algorithm called Weighted-k-means is introduced it can calculate variable weights automatically. But this algorithm is week to f ...
... algorithm cannot select variables automatically because k-means treat all variables equally in clustering process it result in poor clustering. New k-means type clustering algorithm called Weighted-k-means is introduced it can calculate variable weights automatically. But this algorithm is week to f ...
Using Distributed Data Mining and Distributed Artificial
... generation of individual models, where each agent applies the same machine learning algorithm to different subsets of data for acquiring rules, (3) cooperation with the exchange of messages, and (4) construction of an integrated model, based on results obtained from the agents’ cooperative work. The ...
... generation of individual models, where each agent applies the same machine learning algorithm to different subsets of data for acquiring rules, (3) cooperation with the exchange of messages, and (4) construction of an integrated model, based on results obtained from the agents’ cooperative work. The ...
Robotics Process Automation: Optimizing Today`s Banking
... That monitoring of patterns and events is performed by virtual engineers (robots) that can actually learn by observing process-based activities undertaken by human engineers. The subsequent knowledge gathered through machine observation can then be incorporated into future computer inferences made d ...
... That monitoring of patterns and events is performed by virtual engineers (robots) that can actually learn by observing process-based activities undertaken by human engineers. The subsequent knowledge gathered through machine observation can then be incorporated into future computer inferences made d ...
![[slides] Kernels and clustering](http://s1.studyres.com/store/data/004208335_1-990c8ce2efe99730694ed35e841f416e-300x300.png)
[slides] Kernels and clustering
... * Fine print: if your kernel doesn’t satisfy certain technical requirements, lots of proofs break. E.g. convergence, mistake bounds. In practice, illegal kernels sometimes work (but not always). ...
... * Fine print: if your kernel doesn’t satisfy certain technical requirements, lots of proofs break. E.g. convergence, mistake bounds. In practice, illegal kernels sometimes work (but not always). ...
Power Point Template - Intelligent Modelling and Analysis
... • Fuzzy sets to represent the opinions for radiologists in analysing two important features from the American College of Radiology Breast Imaging Lexicon [Kovalerchuk et al 1997] • Fuzzy-genetic method to Wisconsin BC diagnosis data. Genetic algorithm was used to generate a fuzzy inference system [P ...
... • Fuzzy sets to represent the opinions for radiologists in analysing two important features from the American College of Radiology Breast Imaging Lexicon [Kovalerchuk et al 1997] • Fuzzy-genetic method to Wisconsin BC diagnosis data. Genetic algorithm was used to generate a fuzzy inference system [P ...
Data mining
... The definition of ANN: ANN is a kind of computing system that is created by hardware or software. ANN used a lot of artificial neuron to simulate the ability of an organism neuron. Artificial neuron is a simple simulation of an organism neuron that gathered input data from external environment or ot ...
... The definition of ANN: ANN is a kind of computing system that is created by hardware or software. ANN used a lot of artificial neuron to simulate the ability of an organism neuron. Artificial neuron is a simple simulation of an organism neuron that gathered input data from external environment or ot ...
An Enterprise Intelligent System Development and Solution
... A. Database Access Layer Components in this layer help to maintain various database connections simultaneously. The core engine converts SQL (Structured Query Language) responses into XML and XML data into SQL queries. It can fetch the data from more than one database and update also. The queries ca ...
... A. Database Access Layer Components in this layer help to maintain various database connections simultaneously. The core engine converts SQL (Structured Query Language) responses into XML and XML data into SQL queries. It can fetch the data from more than one database and update also. The queries ca ...
Nearest Neighbor Voting in High Dimensional Data: Learning from
... xi are feature vectors which reside in some high-dimensional Euclidean space, and yi ∈ c1 , c2 , ..cC are the labels. It can be shown that in the hypothetical case of an infinite data sample, the probability of a nearest neighbor of xi having label c is asymptotically equal to the posterior class pr ...
... xi are feature vectors which reside in some high-dimensional Euclidean space, and yi ∈ c1 , c2 , ..cC are the labels. It can be shown that in the hypothetical case of an infinite data sample, the probability of a nearest neighbor of xi having label c is asymptotically equal to the posterior class pr ...
M.Tech (Full Time) – KNOWLEDGE ENGINEERING
... PURPOSE The course gives a comprehensive understanding on software agents. INSTRUCTIONAL OBJECTIVES This course introduces the students to 1. The characteristics of the agents, 2. The design and implementation of Agents 3. The implementation described in the architecture level. Interacting with Agen ...
... PURPOSE The course gives a comprehensive understanding on software agents. INSTRUCTIONAL OBJECTIVES This course introduces the students to 1. The characteristics of the agents, 2. The design and implementation of Agents 3. The implementation described in the architecture level. Interacting with Agen ...
Is it Possible to Extract Metabolic Pathway
... fingerprint, always remain constant. Most of the metabolites have multiple resonances many of which are split into multiplets as a result of homonuclear proton scalar coupling. This fact is particularly true of proton NMR spectroscopy at clinical field strengths (from 1.5 up to 3 Teslas), where the ...
... fingerprint, always remain constant. Most of the metabolites have multiple resonances many of which are split into multiplets as a result of homonuclear proton scalar coupling. This fact is particularly true of proton NMR spectroscopy at clinical field strengths (from 1.5 up to 3 Teslas), where the ...
A Novel Bayesian Classification Method for Uncertain Data
... classifications, and it is often surprisingly effective. A large number of modifications have been introduced by the statistical, data mining, machine learning, and pattern recognition communities in an attempt to make it more flexible [30]. It is widely used in areas such as text classification and ...
... classifications, and it is often surprisingly effective. A large number of modifications have been introduced by the statistical, data mining, machine learning, and pattern recognition communities in an attempt to make it more flexible [30]. It is widely used in areas such as text classification and ...
State Space Construction by Attention Control
... in class 0, and ml is the number of data such that in class 1. Here, the discriminant analysis generally takes much computational time for a large number of dimensions of the sensory data. Therefore, it is necessary to perform a kind of dimensionality reduction to reduce the size of the sensory data ...
... in class 0, and ml is the number of data such that in class 1. Here, the discriminant analysis generally takes much computational time for a large number of dimensions of the sensory data. Therefore, it is necessary to perform a kind of dimensionality reduction to reduce the size of the sensory data ...
Well Elderly Assessment - Trinity Valley Community College
... Housekeeping: (3) Maintains house alone or with occasional assistance (2) Performs light daily tasks but cannot maintain acceptable levels of cleanliness (1) Needs help with all home maintenance tasks (0) Does not participate in any housekeeping tasks Laundry: (2) Does personal laundry completely (1 ...
... Housekeeping: (3) Maintains house alone or with occasional assistance (2) Performs light daily tasks but cannot maintain acceptable levels of cleanliness (1) Needs help with all home maintenance tasks (0) Does not participate in any housekeeping tasks Laundry: (2) Does personal laundry completely (1 ...