Essays about: "predictive model"

Showing result 31 - 35 of 852 essays containing the words predictive model.

1. 31. Assessment and evaluation of heterogeneity in data from immune infiltration spatial niches in lung cancer

   University essay from Lunds universitet/Matematisk statistik

   Author : Mahta Keivani Najafabadi; [2023]
   Keywords : Mathematics and Statistics;

   Abstract : The protein biomarker expressions in three types of sampled immune INFILTration spatial niches in lung cancer tissue were measured using the new technology Digital Spatial Profiler (DSP). The three types of immune INFILTration that were observed in lung tumors were STROMA identified as immune cells separate from tumor cells, Tertiary lymphoid structures (TLS) identified as dense structures of organized immune cells and finally Infiltraterate where immune cells dispersed among and in direct contact with tumor cells (INFILT). READ MORE

3. 32. Low-No code Platforms for Predictive Analytics

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Soma Karmakar; [2023]
   Keywords : Low code; no code; Predictive analytics; databricks; azure; AWS; Google cloud;

   Abstract : In the data-driven landscape of modern business, predictive analytics plays a pivotal role inanticipating and mitigating customer churn—a critical challenge for organizations. However, thetraditional complexities of machine learning hinder accessibility for decision-makers. READ MORE

4. 33. The Application of Multivariate Statistical Process Control during Industrial Hot Isostatic Pressing Sintering Processes : A Case study at Seco Tools AB

   University essay from Luleå tekniska universitet/Institutionen för ekonomi, teknik, konst och samhälle

   Author : Karl Ericsson; [2023]
   Keywords : Multivariate statistical process control; Batch processes; Quality prediction;

   Abstract : This Master's thesis focuses on improving the understanding and monitoring of the Hot Isostatic Pressing (HIP) sintering process used by Seco Tools AB to manufacture cemented carbides for cutting tools. While essential for producing cutting tools with superior hardness and toughness the HIP sintering process introduces a complex relationship between the selected process parameters and the achieved materials properties. READ MORE

5. 34. Predictive Modeling and Statistical Inference for CTA returns : A Hidden Markov Approach with Sparse Logistic Regression

   University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

   Author : Oskar Fransson; [2023]
   Keywords : Probability theory; Statistical inference; finance; CTA; managed futures; machine learning; statistical learning; stochastic process; sparse logistic regression; Markov Chain Monte Carlo; Hidden Markov model;

   Abstract : This thesis focuses on predicting trends in Commodity Trading Advisors (CTAs), also known as trend-following hedge funds. The paper applies a Hidden Markov Model (HMM) for classifying trends. Additionally, by incorporating additional features, a regularized logistic regression model is used to enhance prediction capability. READ MORE

6. 35. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Luca Colasanti; [2023]
   Keywords : Survival Analysis; Time To Event prediction; Churn retention; Machine Learning; Deep Learning; Customer Clustering; E-commerce; Analisi di sopravvivenza; Previsione del tempo a evento; Ritenzione dall’abbandono dei clienti; Apprendimento automatico; Apprendimento profondo; Segmentazione della clientela; Commercio elettronico; Överlevnadsanalys; Tid till händelseförutsägelse; Churn Prediction; Maskininlärning; Djuplärning; Kundkluster; E-handel;

   Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE