Spremen Nov Data Tab Det

## Overview

Spremen Nov Data Tab Det is a dataset for object detection tasks - it contains Spremen Nov Data Table annotations for 1,447 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Dataset

This dataset was created by liziyun

Released under CC0: Public Domain

Contents

Data for ioos-station-TABS-P for the period 1998/07. 1998/07 time series data for ioos-station-TABS-P platform served via Gulf of America Coastal Observing System (GCOOS) Data Portal.

This data set contains 30-minute resolution surface meteorological and oceanographic data from the Texas Automated Buoy System (TABS) network which is operated by the Geochemical and Environmental Research Group in the Texas A&M University College of Geosciences and the Texas General Land Office Oil Spill Prevention and Response group. There are 6 stations within the network that provide meteorological observations. The stations are located along the Texas Gulf coast. This data set covers the period from 1 June to 31 October 2005. The data are in space delimited ASCII format. NCAR/EOL has conducted no additional quality control on these data.

This dataset consists of all of the ISA-Tab format metadata files accompanying Data Descriptors published in Scientific Data from journal launch in May 2014 to September 2019 inclusive. In the September 2020 the journal transitioned to a JSON-LD format for these metadata files.The dataset consists of a single ZIP archive containing sub-directories for each Data Descriptor's metadata. Each directory is given a unique identifier based on the publication's DOI. More information on the metadata specification can be found on the journal blog, here: http://blogs.nature.com/scientificdata/2014/01/08/scientific-datas-metadata-specification/Prior to release, all investigation files were processed to remove a number of redundant and unnecessary data fields. For this reason, they will differ slightly from the versions still hosted alongside the papers on the Scientific Data journal website. Specifically, the following fields have been removed:* Comment[Subject Keywords]

• Comment[Supplementary Information File Name]

• Comment[Supplementary Information File Type]

• Comment[Supplementary Information File URL]The tool used to perform this processing is freely available on Github: https://github.com/joeasalter/scidata-isatab-cleaner

This data release is a compilation of data that characterize Alberta groundwater springs. It was compiled from several government datasets and reports, and fieldwork conducted by Alberta Geological Survey (AGS) staff members. The source datasets include the digitized Alberta Research Council (ARC) Hydrogeology Map Series, the AGS Springs of Alberta report, ARC water chemistry data, Groundwater Resources Information Services (GWRIS) Index, Alberta Environmental Protection (AEP) springs, AGS Northeastern Alberta (NEALTA) project springs, field work conducted by Dr. J. Toth and R. Stein, and other more recent spring sampling projects. The data release includes field measurements and water chemistry analyses, as well as some isotope data. Where they are available the dataset also includes references to reports for further information. The data is housed within two primary tables that are related to each other in a one-to-many relationship through the unique identifier field, UID. Also included in the data release are four reference tables containing descriptions of certain data attributes.

Data for ioos-station-TABS-X for the period 2014/01. 2014/01 time series data for ioos-station-TABS-X platform served via Gulf of America Coastal Observing System (GCOOS) Data Portal.

This dataset provides information about the number of properties, residents, and average property values for Tab Lane cross streets in Cana, VA.

Dataset

This dataset was created by liziyun

Released under CC0: Public Domain

Contents

This dataset contains the predicted prices of the asset tab and chill over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Inside the spreadsheet are two tabs, "Survey Data" and "Survey Questions - Full Text". On the first tab, you will find that each row (starting on row 2) represents one person who answered the survey, and each column represents a question asked in the community survey. Row 1 of the Data tab contains simplified versions of the survey questions for quick reference. To find the full text of each survey question, click on the "Survey Question - Full Text" tab. The column names used in the "Survey Data" tab appear down the left-hand side of the page, next to the survey question they match.

Dataset card for Text Anonymization Benchmark (TAB) train

  Dataset Summary

This is the training split of the Text Anonymisation Benchmark. As the title says it's a dataset focused on text anonymisation, specifcially European Court Documents, which contain labels by mutltiple annotators.

  Supported Tasks and Leaderboards

[More Information Needed]

  Languages

[More Information Needed]

  Dataset Structure





  Data Instances

[More Information… See the full description on the dataset page: https://huggingface.co/datasets/mattmdjaga/text-anonymization-benchmark-train.

This dataset provides information about the number of properties, residents, and average property values for Tab Road cross streets in Margaretville, NY.

Since its inception in 1920, the Alberta Geological Survey (AGS) has drilled several thousand boreholes across the province. Most were drilled only into the unconsolidated sediments overlying the top of bedrock. In 2010, AGS staff began a project to systematically compile all of the borehole log information into a database. This Digital Data product and its companion Open File Report, OFR 2014-06 are the interim results of this initiative. The dataset comprises three tables: Sources.txt, Boreholes.txt and Intervals.txt, as well as metadata. The Sources table gives summary information about the AGS project for which each borehole was drilled. The Boreholes table gives summary information about each borehole, such as location, drilling method, date, and total depth of the hole. The Intervals table gives descriptive geological information about each distinct geological horizon encountered in the borehole, including lithology and colour of the material. The tables have primary keys on them so they may be loaded into a relational database, GIS system, or geological modelling program. This dataset is an interim release of 266 boreholes.

Inside the spreadsheet are two tabs, "Survey Data" and "Survey Questions - Full Text". On the first tab, you will find that each row (starting on row 2) represents one person who answered the survey, and each column represents a question asked in the community survey. Row 1 of the Data tab contains demographic data and simplified versions of the survey questions for quick reference. Similar questions are grouped into sections marked with unique colors. To find the full text of each survey question, click on the "Survey Question - Full Text" tab. The column names used in the "Survey Data" tab appear down the left-hand side of the page, next to the survey question they match.

NaiveBayes_R.xlsx: This Excel file includes information as to how probabilities of observed features are calculated given recidivism (P(x_ij│R)) in the training data. Each cell is embedded with an Excel function to render appropriate figures. P(Xi|R): This tab contains probabilities of feature attributes among recidivated offenders. NIJ_Recoded: This tab contains re-coded NIJ recidivism challenge data following our coding schema described in Table 1. Recidivated_Train: This tab contains re-coded features of recidivated offenders. Tabs from [Gender] through [Condition_Other]: Each tab contains probabilities of feature attributes given recidivism. We use these conditional probabilities to replace the raw values of each feature in P(Xi|R) tab. NaiveBayes_NR.xlsx: This Excel file includes information as to how probabilities of observed features are calculated given non-recidivism (P(x_ij│N)) in the training data. Each cell is embedded with an Excel function to render appropriate figures. P(Xi|N): This tab contains probabilities of feature attributes among non-recidivated offenders. NIJ_Recoded: This tab contains re-coded NIJ recidivism challenge data following our coding schema described in Table 1. NonRecidivated_Train: This tab contains re-coded features of non-recidivated offenders. Tabs from [Gender] through [Condition_Other]: Each tab contains probabilities of feature attributes given non-recidivism. We use these conditional probabilities to replace the raw values of each feature in P(Xi|N) tab. Training_LnTransformed.xlsx: Figures in each cell are log-transformed ratios of probabilities in NaiveBayes_R.xlsx (P(Xi|R)) to the probabilities in NaiveBayes_NR.xlsx (P(Xi|N)). TestData.xlsx: This Excel file includes the following tabs based on the test data: P(Xi|R), P(Xi|N), NIJ_Recoded, and Test_LnTransformed (log-transformed P(Xi|R)/ P(Xi|N)). Training_LnTransformed.dta: We transform Training_LnTransformed.xlsx to Stata data set. We use Stat/Transfer 13 software package to transfer the file format. StataLog.smcl: This file includes the results of the logistic regression analysis. Both estimated intercept and coefficient estimates in this Stata log correspond to the raw weights and standardized weights in Figure 1. Brier Score_Re-Check.xlsx: This Excel file recalculates Brier scores of Relaxed Naïve Bayes Classifier in Table 3, showing evidence that results displayed in Table 3 are correct. *****Full List***** NaiveBayes_R.xlsx NaiveBayes_NR.xlsx Training_LnTransformed.xlsx TestData.xlsx Training_LnTransformed.dta StataLog.smcl Brier Score_Re-Check.xlsx Data for Weka (Training Set): Bayes_2022_NoID Data for Weka (Test Set): BayesTest_2022_NoID Weka output for machine learning models (Conventional naïve Bayes, AdaBoost, Multilayer Perceptron, Logistic Regression, and Random Forest)

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

11233 Global import shipment records of Samsung Tab with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Inside the spreadsheet are two tabs, "Survey Data" and "Survey Questions - Full Text". On the first tab, you will find all of the questions from the main, community-wide survey, where each column represents a question and each row (starting on row 2) represents one person who answered the survey. Row 1 of the Data tab contains simplified versions of the survey questions for quick reference. To find the full text of each survey question, click on the "Survey Question - Full Text" tab and scroll down until you find the question of interest.

1412900 Global import shipment records of Tab with prices, volume & current Buyer’s suppliers relationships based on actual Global import trade database.