Orange

Orange

von University of Ljubljana

Was ist Orange?

Open-Source-Datenvisualisierung und Machine Learning Suite. Bietet visuelle Programmierung zur Erstellung von Analyse-Workflows.

Orange – Details

University of Ljubljana

http://orange.biolab.si

Orange – Kostenübersicht

Orange bietet eine Gratisversion und eine kostenlose Testversion.

Kostenlose Version

Ja

Gratis Testen

Ja

Einsatz

Installiert - Mac

Installiert - Windows

Training

Persönlich

Live Online

Kundenbetreuung

Online

Orange Funktionen

Data-Mining-Tools
Betrugserkennung
Datenextraktion
Datenvisualisierung
Maschinelles Lernen
Prädiktives Modellieren
Semantische Suche
Statistische Analyse
Text Mining
Verknüpfte-Daten-Management
Analysen/Berichterstattung
Benutzerdefinierte Dashboards
Content-Management
Gefilterte Ansichten
OLAP
Relationales Display
Simulationsmodelle
Visuelle Entdeckung

Orange – Nutzerbewertungen

Zeigt 5 von 8 Nutzerbewertungen

Gesamt
4,1/5
Benutzerfreundlichkeit
4/5
Kundenservice
3,7/5
Funktionen
4,2/5
Preis-Leistungs-Verhältnis
4,3/5
Shahzad M.
Asst. Manager SAP ABAP
Unterhaltungselektronik, 1.001-5.000 Mitarbeiter
Verwendete die Software für: Mehr als 1 Jahr
  • Gesamtbewertung
    5/5
  • Benutzerfreundlichkeit
    4/5
  • Eigenschaften & Funktionalitäten
    4/5
  • Kundenbetreuung
    4/5
  • Preis-Leistungs-Verhältnis
    4/5
  • Wahrscheinlichkeit der Weiterempfehlung
    8/10
  • Quelle des Nutzers 
  • Bewertet am 17.6.2020

"Pros and Cons of orange for Data visualization "

Kommentare: A perfect suit for business statistics, prediction analysis, machine learning and data visualization.
Uses low resources, fast and convenient.

Vorteile: Easy to use and understand to perform the visualization work with large data, purely assists you to predict business insights with machine learning. Graphics and analysis direct you clearly to conclusions/results .
As large data reading is tough and to make conclusion with the raw data is much tough so tools like orange will really help, it is based in data flows configuration which is too handled by user interface.
Machine learning models and anylsis can be too performed on it for roboting.

Nachteile: Graphics controller are lesser like zoom,scroll. 2nd they can't be exported in visual form.
Reliability effects when wrong data is provided but it can't detect like numbers format instead of alphabatic letters.

  • Quelle des Nutzers 
  • Bewertet am 17.6.2020
Lisa L.
Master of Science in Analytics
Hochschulbildung, 13-50 Mitarbeiter
Verwendete die Software für: 6-12 Monate
  • Gesamtbewertung
    4/5
  • Benutzerfreundlichkeit
    4/5
  • Eigenschaften & Funktionalitäten
    4/5
  • Kundenbetreuung
    3/5
  • Preis-Leistungs-Verhältnis
    5/5
  • Wahrscheinlichkeit der Weiterempfehlung
    8/10
  • Quelle des Nutzers 
  • Bewertet am 16.10.2018

"Orange is for non programmers who want to learn Machine Learning!"

Kommentare: Overall my experience with Orange has been fruitful for me as I picked up machine learning concepts without allowing my basic coding knowledge to hinder me. The interface is prettier than weka(another GUI tool for machine learning) There are several preloaded datasets that has already been clean and users can take advantage of those and follow through the documentation that is provided. My favorite one is the titanic dataset that predicts if the person survives or not depending their gender, class and the number of siblings/spouses they have.

Vorteile: The graphical user interface of orange is great for someone who is not a programmer but wants to execute analytic workflows on machine learning on their dataset. The interface is nicely designed and the analytics workflow is easy to create with the use of drag and drop of its widgets. The widgets available are extensive and would enable users to clean, visualize, build models for supervised and unsupervised learning and validate their model. Orange has put together resources for its users to pick up machine learning on their own. There are also several tutorial videos as well on the website.

Nachteile: We aren't able to set.seed in the software which causes results and analysis to not be reproducible. Orange does not provide enough parameters to tweak for advanced users. For instance, the randomForest widget does not allow the user to see which variables have the highest information gain.

  • Quelle des Nutzers 
  • Bewertet am 16.10.2018
Mudssar A.
Asst. Manager Porecurement Quality
Unterhaltungselektronik, 1.001-5.000 Mitarbeiter
Verwendete die Software für: Mehr als 1 Jahr
  • Gesamtbewertung
    4/5
  • Benutzerfreundlichkeit
    3/5
  • Eigenschaften & Funktionalitäten
    3/5
  • Kundenbetreuung
    3/5
  • Preis-Leistungs-Verhältnis
    3/5
  • Wahrscheinlichkeit der Weiterempfehlung
    7/10
  • Quelle des Nutzers 
  • Bewertet am 17.5.2020

"Data Analysis and ML with data Visulization."

Kommentare: Overall good to use if you are expert, data mining,visulization on big data I found perfect but after many practices, mixed GUI and programming so analysis is easy by setting the data flows. in this cost it is better.

Vorteile: Useful tool to analyse big data, while working with regression and hypothesis I found it very helping. perdiction result may be conluded accurately if we know best assigning and configuration of data sets. Machine learning practies can be determined with basic programming.

Nachteile: Advance analysis is not so easy, it do not give any error even on wrong data. some times slower the system while working on data.

  • Quelle des Nutzers 
  • Bewertet am 17.5.2020
Abdul B.
Manager Porecurement & Inventory
Unterhaltungselektronik, 1.001-5.000 Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
  • Gesamtbewertung
    4/5
  • Benutzerfreundlichkeit
    5/5
  • Eigenschaften & Funktionalitäten
    5/5
  • Kundenbetreuung
    5/5
  • Preis-Leistungs-Verhältnis
    5/5
  • Wahrscheinlichkeit der Weiterempfehlung
    9/10
  • Quelle des Nutzers 
  • Bewertet am 2.6.2020

"Business Statistics on visualization and Machine learning with Orange"

Kommentare: Overall an effective tool for business to analyze statistics by visualization, specially a few clicks can conclude million/billion of records and hence you can proceed,optimise and decide the business/project scenioris.
Effective usage by predictions and categorised machine learning in AI.

Vorteile: Best tool to perform visual analyze the deep statistics of a large data with a few steps, easy to use, UI is accordingly designed.
Faster in operation with recommended system specification.
Data input format is optimisation based and easier to conclude the prediction results.
Supervised/unsupervised Machine learning is easier through basic programs.
Best fo forecasting,predictions,SPCs.

Nachteile: Not such a cons I found it, but only it can not configured with live data, any attachment with Mysql DB would be a plus point to work on live visualization.

  • Quelle des Nutzers 
  • Bewertet am 2.6.2020
Awais I.
Production & Planning Executive
Bekleidung & Mode, 10.001+ Mitarbeiter
Verwendete die Software für: Mehr als 2 Jahre
  • Gesamtbewertung
    4/5
  • Benutzerfreundlichkeit
    4/5
  • Eigenschaften & Funktionalitäten
    5/5
  • Kundenbetreuung
    3/5
  • Preis-Leistungs-Verhältnis
    4/5
  • Wahrscheinlichkeit der Weiterempfehlung
    9/10
  • Quelle des Nutzers 
  • Bewertet am 27.5.2020

"Business anayltics and data visulization with Orange"

Kommentare: Overall found very useful and sophisticated, it fullfilled all my requirements which were comletely based on SPC and forecasting.
On a few clicks I can analyze/visulize million of records within very short time. Recommended for Planning and forecastng purposes.

Vorteile: A powerful tool to analyze,perdict and visualize large data with a few configuration of data varibales, smooth and fast while working. Forecasting, trends can be simulated by visualization on it.
Graphs settings are not typical that are fixed, In Orange we can modify axis,scale and data accordingly.

Nachteile: Charts, visulized items cant be exported or copied in raw form, only screen short etc. is captured, which is some how does not look better when resizing in a presentation.
Tracing error in data is difficult becuase we have to see it manual.

  • Quelle des Nutzers 
  • Bewertet am 27.5.2020