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Hotel Nassauer Hof
The Hotel Nassauer Hof seen from Bowling Green park
General information
Location
Wiesbaden
Address
Kaiser-Friedrich-Platz 3-4 65183 Wiesbaden
Opening
1813
Technical details
Floor count
5
Other information
Number of rooms
135
Number of suites
23
Number of restaurants
1
Website
www.nassauer-hof.de
Nassauer Hof is a luxury five-star superior hotel in Wiesbaden, Germany, and member of the international association The Leading Hotels of the World as well as the German association Selektion Deutscher Luxushotels . The property was built in 1813 and is situated across from the Wiesbaden Kurhaus and at the end of Wiesbaden's luxury shopping avenue Wilhelmstrasse.
Contents
1Restaurant
2Notable guests
3References
4External links
Restaurant[edit]
Without a break, the hotel's restaurant ENTE has been awarded with a Michelin star for more than 30 years.[1]
Notable guests[edit]
Fyodor Dostoyevsky
Wilhelm II
Nicholas II
Walther Rathenau
Paul von Hindenburg
John F. Kennedy
Richard Nixon
Audrey Hepburn
Luciano Pavarotti
Reinhold Messner
Dalai Lama
Vladimir Putin
Willem-Alexander & Máxima of the Netherlands
References[edit]
^"Ente". Nassauer Hof. Retrieved March 9, 2013.
External links[edit]
Media related to Nassauer Hof at Wikimedia Commons
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up vote 2 down vote favorite There is a clear pattern that show for two separate subsets (set of columns); If one value is missing in a column, values of other columns in the same subset are missing for any row. Here is a visualization of missing data My tries up until now, I used ycimpute library to learn from other values, and applied Iterforest. I noted, score of Logistic regression is so weak (0.6) and thought Iterforest might not learn enough or anyway, except from outer subset which might not be enough? for example the subset with 11 columns might learn from the other columns but not from within it's members, and the same goes for the subset with four columns. This bar plot show better quantity of missings So of course, dealing with missings is better than dropping rows because It would affect my prediction which does contain the same missings quantity relatively. Any better way to deal with these ? [EDIT] The nullity pattern is confirmed: machine-learning cor...