TreeGrad: Transferring Tree Ensembles to Neural Networks

Gradient Boosting Decision Tree (GBDT) are popular machine learning algorithms with implementations such as LightGBM and in popular machine learning toolkits like Scikit-Learn. Many implementations can only produce trees in an offline manner and in a greedy manner. We explore ways to convert existing GBDT implementations to known neural network architectures with minimal performance loss in order to allow decision splits to be updated in an online manner and provide extensions to allow splits points to be altered as a neural architecture search problem. We provide learning bounds for our neural network.Comment: Technical Report on Implementation of Deep Neural Decision Forests Algorithm. To accompany implementation here: https://github.com/chappers/TreeGrad. Update: Please cite as: Siu, C. (2019). "Transferring Tree Ensembles to Neural Networks". International Conference on Neural Information Processing. Springer, 2019. arXiv admin note: text overlap with arXiv:1909.1179

Synthesis and Characterization of Eu, Tb doped Y2SiO5 Phosphors

The structural and the optical properties of Terbium and Europium doped yttrium silicate phosphor particles were analyzed. The samples were prepared through solid state reaction method and investigated in a doping concentration of Tb(2%) and Eu(1.5%). The prepared phosphors are characterized using X-ray diffraction (XRD), SEM.FTIR and PL emission of Y2SiO5 phosphor doped with Tb(2%) and Eu(1.5%) was studied. The observed PL emission is at 380 nm followed by the emissions with good intensity at 487, 545, 586, 613 and 622nm. The present phosphor may be a good candidate for LED

Sex Differences in the uptake of health care services in persons with disabilities. Identifying barriers to health care access

Background Evidence suggests that disability is more common among vulnerable populations which include women, elderly and children. And people with disabilities face widespread barriers in accessing services in relation to health, education, employment and transport. This study looks at the barriers women with disability face in accessing heath care services. The present study was undertaken in two states of India - Andhra Pradesh (Medak district) and Karnataka (Bidar). This is a descriptive study with a nested case control for comparison of access to health, education and employment status among those with and without disability The study was funded by CBM South Asia Regional Office (SARO) and was technically supported by CBM SARO Aim The main aim of the study was to look into whether women with disability have equitable access to health care in India and if there are disparities in access, the underlying causes and reasons for the same

Common Coronary Anomalies on MDCT

Coronary artery anomalies are rare, and the incidence is around 1 to 2% in the general population. Majority of the patients are asymptomatic and detected while investigating another clinical issue. A few anomalies may be life-threatening due to the malignant course with potential for ischemia and even sudden death. Multidetector computed tomography (MDCT) has high accuracy in detecting these anomalies because of volume rendering (VR) and multiplanar reconstruction (MPR). ‘High take-off’, origin of the coronary artery from the opposite or noncoronary cusp with anomalous course and coronary artery fistula are three most frequent anomalies. MDCT can be a useful screening tool in the study of coronary anomalies

Automatic Induction of Neural Network Decision Tree Algorithms

This work presents an approach to automatically induction for non-greedy decision trees constructed from neural network architecture. This construction can be used to transfer weights when growing or pruning a decision tree, allowing non-greedy decision tree algorithms to automatically learn and adapt to the ideal architecture. In this work, we examine the underpinning ideas within ensemble modelling and Bayesian model averaging which allow our neural network to asymptotically approach the ideal architecture through weights transfer. Experimental results demonstrate that this approach improves models over fixed set of hyperparameters for decision tree models and decision forest models.Comment: This is a pre-print of a contribution "Chapman Siu, Automatic Induction of Neural Network Decision Tree Algorithms." To appear in Computing Conference 2019 Proceedings. Advances in Intelligent Systems and Computing. Implementation: https://github.com/chappers/automatic-induction-neural-decision-tre

Common Coronary Anomalies on MDCT

Coronary artery anomalies are rare, and the incidence is around 1 to 2% in the general population. Majority of the patients are asymptomatic and detected while investigating another clinical issue. A few anomalies may be life-threatening due to the malignant course with potential for ischemia and even sudden death. Multidetector computed tomography (MDCT) has high accuracy in detecting these anomalies because of volume rendering (VR) and multiplanar reconstruction (MPR). ‘High take-off’, origin of the coronary artery from the opposite or noncoronary cusp with anomalous course and coronary artery fistula are three most frequent anomalies. MDCT can be a useful screening tool in the study of coronary anomalies

Regularizing soft decision trees

Recently, we have proposed a new decision tree family called soft decision trees where a node chooses both its left and right children with different probabilities as given by a gating function, different from a hard decision node which chooses one of the two. In this paper, we extend the original algorithm by introducing local dimension reduction via L-1 and L-2 regularization for feature selection and smoother fitting. We compare our novel approach with the standard decision tree algorithms over 27 classification data sets. We see that both regularized versions have similar generalization ability with less complexity in terms of number of nodes, where L-2 seems to work slightly better than L-1.Publisher's VersionAuthor Post Prin

Synthesis and Characterization of Er Doped CaZrO3 Phosphors

The present paper reports the synthesis and Photoluminescence (PL) studies of the Er rare earth ions doped in CaZrO3 phosphor at a concentration of 2 mol%. Starting materials like Calcium carbonate (CaCO3), Zirconium oxide(ZrO2),Erbium Oxide (Er2O3). The samples were prepared by the conventional solid-state reaction method, which is the most suitable for large-scale product ion. The received phosphor samples were characterized using XRD, SEM and PL techniques. Undoped CaZrO3 exhibits good photoluminescence emission. The PL emission mainly concentrates around 467 nm, when excited with 254 nm wavelengths. The CaZrO3 phosphor, when doped with Er the PL emission was observed from 400 to 560 nm range peaks around 527 ,531,545 and 553nm with high intensity. The present phosphor can act as host for greenlight emission in compact fluorescent (CFL) and fluorescent lamps

Aiding first incident responders using a decision support system based on live drone feeds

In case of a dangerous incident, such as a fire, a collision or an earthquake, a lot of contextual data is available for the first incident responders when handling this incident. Based on this data, a commander on scene or dispatchers need to make split-second decisions to get a good overview on the situation and to avoid further injuries or risks. Therefore, we propose a decision support system that can aid incident responders on scene in prioritizing the rescue efforts that need to be addressed. The system collects relevant data from a custom designed drone by detecting objects such as firefighters, fires, victims, fuel tanks, etc. The drone autonomously observes the incident area, and based on the detected information it proposes a prioritized based action list on e.g. urgency or danger to incident responders

Spot sputum samples are at least as good as early morning samples for identifying Mycobacterium tuberculosis

Background The use of early morning sputum samples (EMS) to diagnose tuberculosis (TB) can result in treatment delay given the need for the patient to return to the clinic with the EMS, increasing the chance of patients being lost during their diagnostic workup. However, there is little evidence to support the superiority of EMS over spot sputum samples. In this new analysis of the REMoxTB study, we compare the diagnostic accuracy of EMS with spot samples for identifying Mycobacterium tuberculosis pre- and post-treatment. Methods Patients who were smear positive at screening were enrolled into the study. Paired sputum samples (one EMS and one spot) were collected at each trial visit pre- and post-treatment. Microscopy and culture on solid LJ and liquid MGIT media were performed on all samples; those missing corresponding paired results were excluded from the analyses. Results Data from 1115 pre- and 2995 post-treatment paired samples from 1931 patients enrolled in the REMoxTB study were analysed. Patients were recruited from South Africa (47%), East Africa (21%), India (20%), Asia (11%), and North America (1%); 70% were male, median age 31 years (IQR 24–41), 139 (7%) co-infected with HIV with a median CD4 cell count of 399 cells/μL (IQR 318–535). Pre-treatment spot samples had a higher yield of positive Ziehl–Neelsen smears (98% vs. 97%, P = 0.02) and LJ cultures (87% vs. 82%, P = 0.006) than EMS, but there was no difference for positivity by MGIT (93% vs. 95%, P = 0.18). Contaminated and false-positive MGIT were found more often with EMS rather than spot samples. Surprisingly, pre-treatment EMS had a higher smear grading and shorter time-to-positivity, by 1 day, than spot samples in MGIT culture (4.5 vs. 5.5 days, P < 0.001). There were no differences in time to positivity in pre-treatment LJ culture, or in post-treatment MGIT or LJ cultures. Comparing EMS and spot samples in those with unfavourable outcomes, there were no differences in smear or culture results, and positive results were not detected earlier in Kaplan–Meier analyses in either EMS or spot samples. Conclusions Our data do not support the hypothesis that EMS samples are superior to spot sputum samples in a clinical trial of patients with smear positive pulmonary TB. Observed small differences in mycobacterial burden are of uncertain significance and EMS samples do not detect post-treatment positives any sooner than spot samples