The pipeline takes 4 different sets of inputs (all in the data/inputs/ directory, possibly in the form of symbolic links), does some preprocessing, stores the results in the data/intermediate/ directory. Once this is all done, we can apply our machine learning technique, output the results...
Repository files navigation README Code of conduct Apache-2.0 license tspDB tspDB enables predictive query functionality in PostgreSQL by building an additional “prediction index” for a collection of time-series of interest. A prediction index will allow for fast data retrieval, but for entries th...
Methods The National Burn Repository (NBR) and the National Trauma Data Bank (NTDB) provided data on 68,661 (54,219 and 14,442, respectively) burn patients that was used to develop and validate, respectively, a predictive model of burn mortality. Logistic regression was used to model the ...
The sensor data are merged with the data from the growing house weighing scales in the cloud repository so a predictive model of average bird weight from the measured environmental data can be calibrated and validated. Furthermore, a time shift can be applied to the environmental data during ...
Repository files navigation README License Code: Data: VPOD_1.1 DOI: Visual Physiology Opsin Database (VPOD) VPOD: A database of opsins and machine-learning models to predict λmax phenotypes. Histogram distributions of Vertebrate and Invertebrate Opsin Light Sensitivity Data - λmax - from VPOD...
After cloning the GitHub repository, pip3 install -e.#Installs the presto-query-predictor package locallypip3 install -r requirements.txt#Installs dependencies An alternative way is to install the package from PyPi, pip3 install presto-query-predictor ...
To get you familiar with tspDB capabilities, we provided a testing function that will create a set of time series tables in youe database. The test function will also create several prediction indices. Run the function from your postgres terminal ...