Negative data
Handling negative data using Data Envelopment Analysis: a directional distance approach applied to higher education
... Traditionally, DEA assumes non-negativity of the inputs and outputs; however, the application of efficiency analysis, dealing with negative data, has been increasingly taken into account in the literature ...
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Evaluating the Efficiency of Firms with Negative Data in Multi-Period Systems: An Application to Bank Data
... while negative data are present; for this matter the current paper proposes an approach for assessing the efficiency of multi-period systems in the presence of positive and negative ...some ...
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A modified DDF-based super-efficiency model handling negative data
... Conventional DEA models are introduced to evaluate DMUs with non-negative data, while in practice there are important DMUs with negative data and they need to be evaluated. Recently, Lin and ...
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The role of artificially generated negative data for quality estimation of machine translation
... for negative data generation, including random generation of sentences from word distributions and the use of translations in low-ranked positions in n-best lists produced by statistical MT (SMT) ...
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A novel radial super-efficiency DEA model handling negative data
... for negative data, inspired by the Silva’s RDM ...handle negative inputs and ...of negative data. As known, in the absence of negative data, the classical super-efficiency ...
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Estimating Most Productive Scale Size with Double Frontiers in Data Envelopment Analysis using Negative Data
... non negative, whereas in many applications, the negative inputs and outputs could be appear as loss when the net profit is an output ...using negative data in this model and other models like ...
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Portfolio Performance Evaluation in a Modified Mean-Variance-Skewness Framework with Negative Data
... on Data Envelopment Analysis, which the variance of the assets had been used as an input to the DEA and expected return and skewness were the ...with negative data for making the best ...
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Effect of Relocation and Rotation on Radial Efficiency Scores for a Partially Negative Data Problem
... Negative data handling has gained a remarkable importance in the literature of Data Envelopment Analysis (DEA) to address many real life ...various Data Envelopment Analysis models are ...
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Generalized Score Matching for Non-Negative Data
... In Section 6.1, we present the theory for our regularized generalized score matching estimators for general pairwise interaction models before going into the details for the special cases of (truncated) GGMs. Next, we ...
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Negative Training Data Can be Harmful to Text Classification
... training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the ...and negative training ...test data are iden- ...
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Improvised Security for EAV data model using Negative Shuffled database
... the data as another column in the database ...with data itself which will increase algorithms ...algorithm data will be shuffled to change the positions so that no data will be there at their ...
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Doctorum Reciproco: Multi-Generational Professionals and Their Sentimentality Towards Reciprocity
... This survey has been used for decades in Germany and has been annually administered by the German Institute for Economic Research (DIW Berlin) since 1984 (DIW Berlin, 2017a). According to DIW Berlin (2017a), this survey ...
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A NOVEL EARLY WARNING SYSTEM USING FUZZY MULTIPLE ATTRIBUTE DECISION MAKING ALGORITHM AND METEOROLOGICAL DATA
... Big Data sentiment ...testing data set, which is 8,500,000 documents including the 4,250,000 positive and the 4,250,000 negative based on our English training data set which is 5,000,000 ...
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Web Sentiment Analysis for Scoring Positive or Negative Words using Tweeter Data
... From the above trend of overall sentiment of various companies, where the overall sentiment for Bharti Airtel went down to negative on 13 th of December, 2013 and it is due to more tweets relating to bad customer ...
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Improved prediction of missing protein interactome links via anomaly detection
... suspicious negative links, thereby reducing the impact of label noise introduced by assigning undiscovered positive links to the class of negative links in the training ...
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Bayesian Finite Mixture Negative Binomial Model for Over-dispersed Count Data with Application to DMFT Index Data
... index data was the main objective of this ...overdispersed data with sub-populations characterized with heterogeneity also the model can handle uncertainty in the data (DMFT index data) it was ...
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Deduplication on Encrypted Big Data in Using HDFS Framework
... of data has many ...implement data de-duplication across an whole an ...Cloud data storage services mostly refer de-duplication, which removing redundant data by storing only single copy of ...
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The RHD gene is highly detectable in RhD negative Japanese donors
... diverse data on the RHD gene of RhD-negative individuals seem to be due to the difference of RhD-negative and RhC-positive frequency between both ...
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Fields and flares : understanding the complex magnetic topologies of solar active regions
... As analytical methods have improved, and more high-resolution magnetic field data has become available, studies have begun to focus more on increasing twist and magnetic helicity as important flare triggers (e.g., ...
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Opinion Mining in a Code Mixed Environment: A Case Study with Government Portals
... number Of Lookups (5) Here, Reps(t) is the token representation obtained by Google news word embedding and number of lookups is equal to the number of tokens from the comments present in the word embedding model. ...
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