AN EFFICIENT DECISION TREE APPROACH FOR OPINION MINING FROM SKEWED TWITTER CORPUS USING CONFISCATE AND SUBSTITUTE TECHNIQUE

2017 ◽  
Vol 73 (1) ◽  
Author(s):  
salina adinarayana ◽  
E. Ilavarasan
Keyword(s):  
Decision Tree ◽  
Opinion Mining ◽  
Tree Approach

scholarly journals Finding Children with High Risk of Non-Vaccination in 92 Low- and Middle-Income Countries: A Decision Tree Approach

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 646
Author(s):  
Thiago M. Santos ◽  
Bianca O. Cata-Preta ◽  
Cesar G. Victora ◽  
Aluisio J. D. Barros
Keyword(s):  
High Risk ◽  
Decision Tree ◽  
Immunization Coverage ◽  
Risk Groups ◽  
Demographic And Health Surveys ◽  
Middle Income ◽  
Agenda 2030 ◽  
Middle Income Countries ◽  
Tree Approach ◽  
Low And Middle Income

Reducing vaccination inequalities is a key goal of the Immunization Agenda 2030. Our main objective was to identify high-risk groups of children who received no vaccines (zero-dose children). A decision tree approach was used for 92 low- and middle-income countries using data from Demographic and Health Surveys and Multiple Indicator Cluster Surveys, allowing the identification of groups of children aged 12–23 months at high risk of being zero dose (no doses of the four basic vaccines—BCG, polio, DPT and measles). Three high-risk groups were identified in the analysis combining all countries. The group with the highest zero-dose prevalence (42%) included 4% of all children, but almost one in every four zero-dose children in the sample. It included children whose mothers did not receive the tetanus vaccine during and before the pregnancy, who had no antenatal care visits and who did not deliver in a health facility. Separate analyses by country presented similar results. Children who have been missed by vaccination services were also left out by other primary health care interventions, especially those related to antenatal and delivery care. There is an opportunity for better integration among services in order to achieve high and equitable immunization coverage.

A Decision Tree Approach to Customer Surveys

2021 ◽  
Author(s):  
Rafael Guerrero ◽  
Navin Dookeram ◽  
Patrick Hosein
Keyword(s):  
Decision Tree ◽  
Tree Approach

Modelling the abundance of three key plant species in New Zealand hill-pasture using a decision tree approach

2009 ◽  
Vol 220 (15) ◽  
pp. 1819-1825 ◽  
Author(s):  
Liqiang Wan ◽  
Baisen Zhang ◽  
Peter Kemp ◽  
Xianglin Li
Keyword(s):  
New Zealand ◽  
Decision Tree ◽  
Plant Species ◽  
Tree Approach

scholarly journals Globally Harmonized Carbon Storage Data

2019 ◽  
Author(s):  
Justin Andrew Johnson
Keyword(s):  
Decision Tree ◽  
Carbon Storage ◽  
Input Data ◽  
Visual Inspection ◽  
Above Ground Biomass ◽  
Tier 1 ◽  
Multiple Input ◽  
Spatial Configurations ◽  
Combination Of Methods ◽  
Tree Approach

AbstractThis paper presents methods and results that combine multiple carbon storage and above-ground biomass datasets using a simple decision tree approach. The resulting dataset combines the positive attributes of the multiple input datasets in order to have global, high-resolution extent while utilizing the best statistical methods where possible. Visual inspection shows very different spatial configurations of carbon storage between the results and the input data, suggesting that combination of methods can improve estimates. The summation of the decision tree result was 336.55 petagrams while the summation of a dataset based on the IPCC Tier 1 method was 502.38 petagrams (49.27% higher than the results from the decision tree).

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