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To create a new source, you need to POST the file containing your data to the source base URL. The file must be attached in the post as a file upload.

This allows you to upload binary files in compressed format (. You can easily do this using curl.

The option -H lets curl set the content type header while the option -X sets the http method. You will get the access token and the refresh token. Google Drive example:Select the option to create source from Google Drive: Allow BigML access to your Google Drive: Get the access token and refresh token: After complete these steps you need to POST to the source endpoint URL an object containing at least the file ID (for Google Drive) or the bucket and the file name (for Google Storage) and the access token.

Including also the refresh token is optional before your access token expires. Including it avoids you to be worried about expiration time. You first need to authorize BigML access from your own Google Apps application.

After the authorization process you will get your access token and refresh token from the Google Authorization Server. Then the process is the same as creating a remote source using BigML application described above. You need to POST to the source endpoint an object containing at least the file ID (for Google Drive) or the bucket and the file name (for Google Storage) and the access token, but in this case you will also need to include the app secret and app client from your App. Again, including the refresh token is optional.

Your values for app client and app secret appear as Client secret and Client ID in Google developers console respectively. This way is specially useful if you want to model small amounts of data generated by an application.

It can be compressed, gzipped, or zipped. You can also use curl to customize your new source with a name and different parser. For example, to create a new source named "my source", without a header and with "x" as the only missing token.

However, if you do specify it, BigML. While the handling of numeric, categorical, or items fields within a decision tree framework is fairly straightforward, the handling of text fields can be done in a number of different ways.

At the source level, BigML.The second and third columns in the table above report the percentages relative to the number of responses (second column) as well as respondents (third column). Thus, the entry 8.

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Suppose in the above example we were only interested in Coke, Pepsi, and Sprite. As pointed out earlier, one way to code the data in that case would be as follows: COKE PEPSI SPRITE. In other words, one variable was created for each soft drink, then a value of 1 was entered into the respective variable whenever the respective drink was mentioned by the respective respondent.

In a sense, we "compact" the three variables Coke, Pepsi, and Sprite into a single variable (Soft Drink) consisting of multiple dichotomies. All of these types of variables can then be used in crosstabulation tables. For example, we could crosstabulate a multiple dichotomy for Soft Drink (coded as described in the previous paragraph) with a multiple response variable Favorite Fast Foods (with many categories such as Hamburgers, Pizza, etc.

As in the frequency table, the percentages and marginal totals in that table can be computed from the total number of respondents as well as the total number of responses. For example, consider the following hypothetical respondent: Gender Coke Pepsi Sprite Food1 Food2 FEMALE 1 1 FISH PIZZA This female respondent mentioned Coke and Pepsi as her favorite drinks, and Fish and Pizza as her favorite fast foods.

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In the complete crosstabulation table she will be counted in the following cells of the table: Food. FEMALE MALE COKE PEPSI SPRITE COKE PEPSI SPRITE X X X X 2 2 This female respondent will "contribute" to (i.

Paired Crosstabulation of Multiple Response Variables. A unique option for tabulating multiple response variables is to treat the variables in two or more multiple response variables as matched pairs. Again, this method is best illustrated with a simple example. Suppose we conducted a survey of past and present home ownership.

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We asked the respondents to describe their last three (including the present) homes that they purchased.

For each home we asked our respondents to write down the number of rooms in the respective house, and the number of occupants.

Here is how the data for one respondent (say case number 112) may be entered into a data file: Case no. Rooms 1 2 3 No. Now suppose we wanted to crosstabulate the number of rooms by the number of occupants for all respondents. We can also treat the two factors in this study (Number of Rooms, Number of Occupants) as multiple response variables.

However, it would obviously not make any sense to count the example respondent 112 shown above in cell 3 Rooms - 5 Occupants of the crosstabulation table (which we would, if we simply treated the two factors as ordinary multiple response variables). In other words, we want to ignore the combination of occupants in the third home with the number of rooms in the first home. This is exactly what will be accomplished if we asked for a paired crosstabulation of these multiple response variables.

The best way to verify that one understands the way in which the respective tables are constructed is to crosstabulate some simple example data, and then to trace how each case is counted. The example section of the Crosstabulation chapter in the manual employs this method to illustrate how data are counted for tables involving multiple response variables and multiple dichotomies. To index Statistica 2300 East 14th Street Tulsa, Oklahoma, 74104 (918) 749-1119 Global Sites Find Office StatSoft Benelux StatSoft Bulgaria Ltd.

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ABOUT CLEMSON (7-1): Senior forward Donte Grantham recorded a double-double with 17 points and 10 rebounds against UNC Asheville, and leads the Tigers in scoring (15. Five Clemson players average in double figures, while the Tigers have allowed just 64. Clemson is third in the ACC in free-throw shooting at 76. The Tigers are off to their best start since opening 2013-14 at 7-1, moving coach Brad Brownell within two victories of 300 for his career. Clemson G Shelton Mitchell led the Tigers in assists in seven of eight games this season, and Clemson has shot 50 percent or better from the field five times.

The Tigers play three more non-conference games before ACC play begins after Saturday, and two are against SEC foes (Florida on Dec.

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In this Article Was this article helpful. All IE versions add extra space at the bottom without this. Chrome renders images pixelated when switching to GPU.All travel details were clearly detailed in materials sent before trip, as well as, received upon arrival.

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The rail journey form Stockholm was particularly lovely - comfortable, fast and quiet trains, gorgeous scenery, and we crossed The Bridge, too. The time spent in each city was just long enough to absorb the essential elements that made each one special, and it was really interesting to be able to compare their similarities and differences.Lissa, United States South Iceland at Leisure, September 2015 Sigfus provided excellent services and even met with us on our first day in Iceland.

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A closer relationship with customersLike many other forms of social media, online review sites give you the chance to develop a closer relationship with your customers.If this parameter is present, the corresponding field will be discretized according to those defined bins, and the remaining discretization parameters will be ignored. The maximum value of the field's distribution is automatically set as the last value in the edges array.

A value object of a Field Discretizations object is composed of any combination of the following properties.

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You can also use curl to customize a new correlation. If you do not specify a range of instances, BigML. If you do not specify any input fields, BigML. Read the Section on Sampling Your Dataset to lean how to sample your dataset. Once a correlation has been successfully created it will have the following properties. The Correlations Object of test has the following properties.

If p-value is greater than the accepted significance level, then then it fails to reject the null hypothesis, meaning there is no statistically significant difference between the treatment groups. It has the following properties: The Chi-Square Object contains the chi-square statistic used to investigate whether distributions of categorical variables differ from one another. This test is used to compare a collection of categorical data with some theoretical expected distribution.

The object has the following properties. ANOVA is used to compare the means of numerical data samples. The ANOVA tests the null hypothesis that samples in two or more groups are drawn from populations with the same mean values. See One-way Analysis of Variance for more information. The object has the following properties: Creating correlation is a process that can take just a few seconds or a few days depending on the size of the dataset used as input and on the workload of BigML's systems.

The correlation goes through a number of states until its fully completed. Through the status field in the correlation you can determine when the correlation has been fully processed and ready to be used to create predictions.

Thus when retrieving a correlation, it's possible to specify that only a subset of fields be retrieved, by using any combination of the following parameters in the query string (unrecognized parameters are ignored): Fields Filter Parameters Parameter TypeDescription fields optional Comma-separated list A comma-separated list of field IDs to retrieve.

To update a correlation, you need to PUT an object containing the fields that you want to update to the correlation' s base URL. Once you delete a correlation, it is permanently deleted. If you try to delete a correlation a second time, or a correlation that does not exist, you will receive a "404 not found" response. However, if you try to delete a correlation that is being used at the moment, then BigML.

To list all the correlations, you can use the correlation base URL. By default, only the 20 most recent correlations will be returned.


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