Decision Trees: Predicting Future Losses for Insurance Data

Big data is a term that has come to the spotlight for companies within recent years. Data analysis and business intelligence have become prominent sectors of companies and agencies. But what is big data? How has it impacted large companies and agencies? Why must it be embraced? The best way to approach utilizing a big data set is to establish a question to answer. For this data set, the question that must be answered is “What variables cause a loss to occur?” To answer this question, first, we must understand what is meant by a “loss”, and take a look at what kind of data we are working with. The data for this project is live, or active, insurance data from National Interstate Insurance. National Interstate Insurance offered this “live” data set for this project as a way to get a head start on statistical analysis. This data set has only been analyzed for this project presently, and will be visited by data analysts in the future for further assessment. The program used for this project is called SPSS. This tool is one of many used in companies to help draw up decision tree models to display data in an easy to navigate form. In this program, the decision trees are modeled by utilizing a feature that provides a few algorithmic options. These algorithms are known as CHAID and CART. Both algorithms result in some form of a decision tree displaying how variables impact the outcome

Metaphorical Illness in Hemingway\u27s Works

Hemingway, through his characters, illustrates the many different genres and functions of disease. More than just inflictors of sadness and pain, disease and injury are part of the human condition. They are undeniable truths that give life to humanity, Hemingway’s characters, and Hemingway himself. As Hemingway writes in Death in the Afternoon, “…all stories, if continued far enough, end in death, and he is no true storyteller who would keep that from you.” Part of Hemingway’s art is acknowledging that there is no true cure. Vitality and death, contentedness and pain, disease and survival all coexist in Hemingway’s writing as one: life

The Infati Data

The ability to perform meaningful empirical studies is of essence in research in spatio-temporal query processing. Such studies are often necessary to gain detailed insight into the functional and performance characteristics of proposals for new query processing techniques. We present a collection of spatio-temporal data, collected during an intelligent speed adaptation project, termed INFATI, in which some two dozen cars equipped with GPS receivers and logging equipment took part. We describe how the data was collected and how it was "modified" to afford the drivers some degree of anonymity. We also present the road network in which the cars were moving during data collection. The GPS data is publicly available for non-commercial purposes. It is our hope that this resource will help the spatio-temporal research community in its efforts to develop new and better query processing techniques

Genomics and Transcriptomics of the sebacinoid fungi Piriformospora indica and Sebacina vermifera

The root endophyte Piriformospora indica and the orchid mycorrhiza Sebacina vermifera (Sebacinales, Basidiomycota) are able to establish a mutualistic symbiosis with plants. Both fungi colonize the root cortex of a wide range of vascular plants, including the monocot barley (Hordeum vulgare) and the dicot Arabidopsis thaliana. Colonization by the fungi results in growth promotion and induced resistance against abiotic and biotic stresses. Fungal development in roots combines biotrophic growth in living plant cells and cell-death associated colonization of dead cortex cells. These features together with the possibility to cultivate the fungi on synthetic media reveal substantial phenotypic plasticity which is reflected in their genomic traits. In this study, the genomes of Piriformospora indica and Sebacina vermifera were characterized. It could be shown that certain gene and functional protein domain expansions occurred in both species. These included proteins predicted to be involved in intra- and extracellular transport (Transporters), proteolysis (Peptidases), degradation of carbohydrates (Hydrolases) and non-destructive carbohydrate binding (Lectins). Additionally, a novel family of small secreted proteins was identified in P. indica which is characterized by regular distributed histidine and alanine residues and a conserved seven amino acid motif ("RSIDELD") at the C-terminus. On the other side, the number proteins involved in secondary metabolism, in particular polyketide and nonribosomal peptide synthetases, were shown to be strongly reduced in both fungi which is indicative of the non pathogenic character of P. indica and S. vermifera. By using microarrays and RNA-sequencing, a time- and host-specific expression of genes could be shown in P. indica during colonization of barley- or Arabidopsis roots. A first comparative analyses of genes expressed in S. vermifera and P. indica during colonization of Arabidopsis suggests that defined differences exist during the colonization of this host by both analysed fungi