Datasets for the Landscape Susceptibility Models
Landscape susceptibility to large fires
... spatial susceptibility of forests to fire in the short term (Taylor and Alexander, ...anticipating landscape susceptibility to large ...of landscape dryness and fire weather into a single ...
253
GEval: Tool for Debugging NLP Datasets and Models
... ML Models – general idea Creating an ML model is not a one-off act, but a whole continuous process, in which data scientist or ML engineer should analyze what are the weakest points of a model and try to improve ...
9
Datasets, features, learning, and models in visual recognition
... A strategy for building large scale datasets is to ask people on the Internet to label images. There are currently billions of Internet users among whom to recruit volun- teers. LabelMe [26] is a public online ...
118
Macaque models of enhanced susceptibility to HIV
... HIV Susceptibility Nonhuman Primate ...macaque models of enhanced susceptibility to HIV ...the susceptibility enhancement factor tested in the ...increased susceptibility is observed, a ...
9
A Survey On Visual Questioning Answering : Datasets, Approaches And Models
... VQA models are proposed over time which are focused on datasets such as VQA, MS -COCO, Flicker30k ...the models also depend on the type of question ...different datasets available for VQA ...
5
THE LANDSCAPE OF MEDICAID ALTERNATIVE PAYMENT MODELS
... bundled payments in which each provider receives directly from the state a defined rate for its portion of the episode. Alternatively, a single payment may be made to the entire team of providers who cared for a patient ...
7
Predictive Models for Bariatric Surgery Risks with Imbalanced Medical Datasets
... 2.2 Feature Selection Given each outcome, not all features are of significant influence on the out- come. In fact, considering irrelevant features may produce less-accurate clas- sification results and can lead to biased ...
32
Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models
... large datasets, starting with the pioneering work of Forni et ...factor models have produced fairly accurate forecasts when compared with standard benchmarks, such as AR or VAR based predictions, for ...
37
The genomic landscape of testicular germ cell tumours: from susceptibility to treatment.
... TGCT susceptibility, with disease risk enshrined in the co-inheritance of multiple risk variants, many of which are common 18 ...genomic datasets suggest ...
25
Genetic landscape of multiple sclerosis susceptibility by leveraging multi-omics data
... animal models in disease study, EAE has limitations; as it is heterogenous with respect to induction methods and pathological feature; and its utility depends on using the appropriate model to answer specific ...
60
Remote Sensing Procedures to Update Forested Geospatial Datasets after a Landscape Altering Event
... the landscape, by hiding the burn impacts to the shrub and tree ...geospatial datasets by indicating and classifying long term change resulting from a fire is the objective of this research, using Landsat ...
178
Spatially explicit models in landscape and species management
... why landscape models are developed with a degree of spatial detail and realism that seems extreme compared for instance to a metapopulation ...individual-based models (IBMs) in ecology in the course ...
44
Web application development landscape: technologies and models
... CMS-based Web applications as a Web application for the management and control of content.. Web Application Conceptual Architecture[r] ...
32
Estimation and forecasting in vector autoregressive moving average models for rich datasets
... 1 Introduction The use of large arrays of economic indicators to forecast key macroeconomic variables has become very popular recently. Economic agents consider a wide range of information when they construct their ...
41
Assessing State of the Art Sentiment Models on State of the Art Sentiment Datasets
... several models on six different benchmarks, which belong to dif- ferent domains and additionally have dif- ferent levels of granularity (binary, 3-class, 4-class and ...across datasets and that both LSTMs ...
11
Investigating the Effect of Lexical Segmentation in Transformer based Models on Medical Datasets
... 4.4 BioBERT versus Medical Vocab Although trained similarly, all the BioBERT mod- els outperformed our pretrained models across all datasets. For a direct comparison, we compare BioBERT v1.1 PubMED as this ...
7
A New Method for Determining the Number of Factors in Factor Models with Large Datasets
... Moving on to Table 2 we see that both ME and the information criteria work well. There is no underestimation for the criteria but there could not be any anyway as the true number of factors is equal to the minimum one ...
24
AI based cancer detection models using primary care datasets
... prediction models using the patient’s medical history from primary care data can be a useful decision tool for early cancer ...AI models that can be used to detect cancer 3 months earlier than current ...
9
Estimation and forecasting in vector autoregressive moving average models for rich datasets
... VARMA models are able to capture two important features from these two groups of ...VARMA models parsimoniously account for sample correlation profiles of different shapes than the geometrically declining ...
42
Induction of comprehensible models for gene expression datasets by subgroup discovery methodology
... Multi-class cancer domain: Comparing predictive accuracy and number of involved genes for selected predictors obtained by the subgroup discovery approach (SD) and by support vector machi[r] ...
16