Search results for "data science"
epub, pdf |eng | 2014-12-08 | Author:Manas A. Pathak [Pathak, Manas A.]
Fig. 5.3Box plot of BIRTHS2010 and DEATHS2010 for micropolitan statistical areas > boxplot(data.micro$BIRTHS2010,data.micro$DEATHS2010, names=c(’BIRTHS2010’,’DEATHS2010’)) We do not need to set show.names=T when we are calling box plot for multiple variables. ...
( Category:
Mathematics
November 28,2017 )
mobi, epub |eng | | Author:2016
Conducting a hypothesis test There are multiple types of hypothesis tests out there, and among them are dozens of different procedures and metrics. Nonetheless, there are five basic steps that ...
( Category:
Computer Science
November 20,2017 )
azw3, epub |eng | 2017-05-04 | Author:Grigorev, Alexey [Grigorev, Alexey]
for (String line : lines) { String[] split = line.split("t"); String url = split[3]; Optional<String> html = urls.get(url); if (!html.isPresent()) { continue; } org.jsoup.nodes.Document jsoupDoc = Jsoup.parse(html.get()); Element body = ...
( Category:
Databases & Big Data
November 20,2017 )
epub, mobi |eng | | Author:2016
Given such input, the function wraps some other complex functions. It creates n-iterations, training a model of the n-cross-validation in-samples, testing the results, and storing scores derived at each iteration ...
( Category:
Programming Languages
November 3,2017 )
azw3 |eng | 2017-07-07 | Author:Reese, Richard M. & Reese, Jennifer L. & Grigorev, Alexey [Reese, Richard M.]
Module 2 Mastering Java for Data Science Building Data Science Applications in Java Data Science Using Java This book is about building data science applications using the Java language. In ...
( Category:
Databases & Big Data
October 29,2017 )
epub, mobi |eng | 2017-07-06 | Author:Richard M. Reese & Jennifer L. Reese & Alexey Grigorev [Reese, Richard M.]
( Category:
Databases & Big Data
October 29,2017 )
azw3, epub |eng | 2016-07-12 | Author:Jacobs, Dave [Jacobs, Dave]
print(c8_mydata_3) Figure 8.19 Inputted values Now, the model can be applied to this dataset to create the prediction. The results can be seen in Figure 8.20 and show that for ...
( Category:
Marketing & Sales
October 28,2017 )
azw3 |eng | 2015-05-02 | Author:Thomas W. Miller [Miller, Thomas W.]
The linear regression of sales on competition, population, and income is summarized in table 13.1. Variance inflation factors computed for this problem show that multicollinearity is not an issue. Diagnostic ...
( Category:
other
October 26,2017 )
epub |eng | 2015-05-02 | Author:Miller, Thomas W.
The linear regression of sales on competition, population, and income is summarized in table 13.1. Variance inflation factors computed for this problem show that multicollinearity is not an issue. Diagnostic ...
( Category:
Marketing & Sales
October 26,2017 )
epub |eng | 2017-06-15 | Author:Michael R. Brzustowicz, PhD
Unit normal scaling Unit normal scaling is also known as a z-score. It rescales every data point in a column such that it is a member of unit normal distribution ...
( Category:
Databases & Big Data
October 6,2017 )
epub, pdf |eng | 0101-01-01 | Author:Second Edition [Edition, Second]
See also The matplotlib home page at http://matplotlib.org/ The groupby documentation at http://pandas.pydata.org/pandas-docs/stable/groupby.html Chapter 7. Working with Social Graphs In this chapter, we will cover: Preparing to work with social ...
( Category:
Databases & Big Data
September 17,2017 )
epub |eng | 2017-09-02 | Author:Jeffrey S. Saltz & Jeffrey M. Stanton
Next, we can change formats and data types as needed. We can remove the dots from in front of the state names very easily with str_replace(): > testFrame$stateName <- + ...
( Category:
other
September 13,2017 )
mobi, epub |eng | | Author:2015
This is the function to find the closest prototype vector for a given vector:def find_closest(in_vector,proto_vectors): closest = None closest_distance = 99999 for p_v in proto_vectors: distance = euclidean_distances(in_vector,p_v.p_vector) if distance ...
( Category:
Programming Languages
September 6,2017 )
epub |eng | 2015-04-14 | Author:Grus, Joel
For example, if 50% of spam messages have the word viagra, but only 1% of nonspam messages do, then the probability that any given viagra-containing email is spam is: A ...
( Category:
Databases & Big Data
September 3,2017 )
epub |eng | 2016-12-12 | Author:Wickham, Hadley & Grolemund, Garrett
as.duration(h_age) #> [1] "1167350400s (~36.99 years)" Durations come with a bunch of convenient constructors: dseconds(15) #> [1] "15s" dminutes(10) #> [1] "600s (~10 minutes)" dhours(c(12, 24)) #> [1] "43200s (~12 ...
( Category:
Software
September 3,2017 )
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