Your question might be answered by sellers, manufacturers, or customers who bought this product. Please make sure that you are posting in the form of a question. Please enter a question. The GB40 is an ultra-portable, lightweight, and compact portable lithium car battery jump starter pack for volt batteries.
With it, you can safely jump start a dead battery in seconds - up to 20 times on a single charge. It's a mistake-proof portable car battery jump starter battery booster pack, making it safe for anyone to use and features spark-proof technology, as well as reverse polarity protection.
The GB40 portable car battery jump starter integrates with a high-output lumen LED flashlight with 7 light modes. Including low, medium, high, flashing, strobe, and emergency SOS. It can hold its charge for up to one year without being recharged.Kg to lbs and stone
Its internal battery can be used to recharge any personal mobile devices like smartphones, tablets, or any other USB device, can be recharged by any powered USB port. It's rated at amps, and suitable for use on gasoline engines up to 6 Liters and diesel engines up to 3 Liters, such as a car, boat, lawnmower, and more. Included is the GB40 battery booster jump starter pack, heavy-duty battery clamps, USB charging cable, volt USB car charger, microfiber storage bag, a 1-year limited, and lifetime customer support.
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Recommended for gas engines up to 6 Liters and diesel engines up to 3 Liters for cars, boats, lawn mowers and more. Mistake-proof and safe for anyone to use with spark-proof technology and reverse polarity protection. With multiple luminosity settings, it is immediately adaptable to a variety of situations. Using it's powerful wash light will help you see your engine, help you change a tire at night, or even warn oncoming traffic when you are in need of roadside assistance.
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Create Account. Where to Buy About Partner. Add to Cart -OR. In Stock. UPC: 2. It features a patented safety technology that provides spark-proof connections and reverse polarity protection making safe and easy for anyone to use. It's a powerful battery booster that doubles as a portable power source for recharging USB devices, like a smartphone, tablet and more.
Designed for a car, boat, RV, truck and more with gas engines up to 6 liters, and diesel engines up to 3 liters. Compact, yet powerful lithium jump starter rated at 1, Amps - up to 20 jump starts on a single charge. An ultra-safe and mistake-proof design with spark-proof technology and reverse polarity protection, which allow it to safely connect to any battery.
Recharge your personal devices on the go, like smartphones, tablets, e-watches and more - up to 4 smartphone recharges. Designed for gas engines up to 6 Liters and diesel engines up to 3 Liters for cars, boats, lawn mowers and more. Write Review.
Yes, I recommend this product. Safely jump start a dead battery in seconds - up to 20 times on a single charge. Technical Specifications. What's In The Box. Starting Current. Internal Battery. Gas Engine Rating. Diesel Engine Rating. Additional products to consider.
You have added this item to your cart. Update Quantity. Have everything you need?Let's also not forget about the USB power port which is capable of recharging virtually any USB device, including smartphones and tablets.
Based on advice and plenty of reviews, I made a great choice. Rating Required Select Rating 1 star worst 2 stars 3 stars average 4 stars 5 stars best. Review Subject Required. Comments Required. Current Stock:. Qty Decrease Quantity: Increase Quantity:. A: Nothing, it is perfectly safe and there will be no sparks.
The entire NOCO Boost series has built in sensors that prevent power from being delivered, unless a battery is detected Q: How long does it hold a charge? For optimal performance, it is recommended to charge the device at least every months, after initial charge. Q: Can it recharge my branded smartphone?
GB40 NOCO Boost Jump Starter
A: Yes. It can recharge all generations of smartphones on the market, as well as HD action cameras, tablets, music players, wireless speakers and more. Q: Does it have any limitations on car engine size for jump starting? A: The GB40 unit is charged via a micro-usb port on the input side of the unit. You can re-charge the unit through either an auxiallary port in a vehicle or with a USB style charger cell phone charger.
Q: What type of batteries can I use this on? This unit is not designed to jump start lithium motorcycle or car batteries. Frequently Bought Together. Out of stock. Add to Cart. High quality product.
Not yet used.However, if you try to delete an anomaly score that is being used at the moment, then BigML. To list all the anomaly scores, you can use the anomalyscore base URL. By default, only the 20 most recent anomaly scores will be returned. You can get your list of anomaly scores directly in your browser using your own username and API key with the following links.
You can also paginate, filter, and order your anomaly scores. Association Sets are useful to know which items have stronger associations with a given set of values for your fields. The similarity score then is multiplied by the selected association measure (confidence, leverage, support, lift, or coverage) to create a similarity-weighted score and finally return a ranking of the predicted items.
You can also list all of your association sets.S. a. chakraborty wikipedia
You can use curl to customize new association sets. Once an association set has been successfully created it will have the following properties. Creating an association set is a near real-time process that take just a few seconds depending on whether the corresponding association has been used recently and the workload of BigML's systems. The association set goes through a number of states until its fully completed.
Through the status field in the association set you can determine when the association set has been fully processed and ready to be used. Most of the times association sets are fully processed and the output returned in the first call.
These are the properties that an association set's status has:To update an association set, you need to PUT an object containing the fields that you want to update to the association set' s base URL. Once you delete an association set, it is permanently deleted. If you try to delete an association set a second time, or an association set that does not exist, you will receive a "404 not found" response.
However, if you try to delete an association set that is being used at the moment, then BigML. To list all the association sets, you can use the associationset base URL. By default, only the 20 most recent association sets will be returned.To get the final number of candidate fields we round down to the nearest integer, but if the result is 0 we'll use 1 instead. Sets the number of random fields considered when randomize is true. Example: 10 randomize optional Boolean,default is false Setting this parameter to true will consider only a subset of the possible fields when choosing a split.
See the Section on Random Decision Forests below. The range of successive instances to build the model. See the Section on Sampling below. So, if it is 3, then a both children of a new split must have 3 instances supporting them. Since instances may have non-integer weights, non-integer values are valid. Example: 16 tags optional Array of Strings A list of strings that help classify and index your model. By default, rows from the input dataset are deterministically shuffled before being processed, to avoid inaccurate models caused by ordered fields in the input rows.
Since the shuffling is deterministic, i. However, you can modify this default behaviour by including the ordering argument in the model creation request, where "ordering" here is a shortcut for "ordering for the traversal of input rows". The row range is specified with the range argument defined in the Section on Arguments above.
To specify a sample, which is taken over the row range or over the whole dataset if a range is not provided, you can add the following arguments to the creation request: Finally, note that the "ordering" of the dataset described in the previous subsection is used on the result of the sampling. The default is false.
When randomized, the model considers only a subset of the possible fields when choosing a split. The size of the subset will be the square root of the total number of input fields.
So if there are 100 input fields, each split will only consider 10 fields randomly chosen from the 100. Every split will choose a new subset of fields. Although randomize could be used for other purposes, it's intended for growing random decision forests.
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To grow tree models for a random forest, set randomize to true and select a sample from the dataset. Traditionally this is a 1. Once a model has been successfully created it will have the following properties.
This will be 201 upon successful creation of the model and 200 afterwards. Make sure that you check the code that comes with the status attribute to make sure that the model creation has been completed without errors. This is the date and time in which the model was created with microsecond precision. It has an entry per each field type (categorical, datetime, numeric, and text), an entry for preferred fields, and an entry for the total number of fields.
It includes a very intuitive description of the tree-like structure that makes the model up and the field's dictionary describing the fields and their summaries. In a future version, you will be able to share models with other co-workers or, if desired, make them publicly available. This is the date and time in which the model was updated with microsecond precision. A Model Object has the following properties: Creating a model 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 model goes through a number of states until its fully completed. Through the status field in the model you can determine when the model has been fully processed and ready to be used to create predictions. Support is a number from 0 to 1 that specifies the minimum fraction of the total number of instances that a given branch must cover to be retained in the resulting tree. If you repeat the support parameter in the query string, the last one is used.Maybe Azshara will hang around as well.
We could possibly be seeing something that would expand on the lore of the void, as it has been explored more in Legion. It will be revealed that the foolish surface dwellers of Azeroth have been ignoring their real enemy. N'zoth rises, and with him the Black Empire will once more dominate the pathetic mortal races of Azeroth. N'dhgi ghu'hul uh'nah belore.
I hope the next expansion will be about old gods. We've been given so many hints throughout the expansion it would be a shame not to. I can't imagine that they wouldn't reveal the expansion. Hopefully as part of that, they will include subraces for all races. I'm hoping they reveal the next expansion. I'm HOPING a new race will be added, as we haven't had one in quite some time. I think that they will reveal something that most people aren't expecting,like the backside of azeroth or another island with old god issues (like pandaria) or a 5th old god and i think that they will reveal one of those.
I believe we will finally see a Kul Tiras related expansion since all the data discovered points to that. Also, I hope for some Old Gods, Jaina's return, Zandalari maybe. Ive been dreaming of this for over 4 years now: Panda Druids. Blizzard please just let me give you that race change money and let me be a bear bear. I hope Jaina or Azshara get some love for the next xpac. And maybe some sub-races that mentioned recently. Blizzard Entertainment Student Art Contests 2017 Be Prepared.
More gender choices coming. Ptr Client nicht instalierbar Best WoW Joke: Go New Player - Levelling How do I contact a GM in game. Let us know your thoughts by leaving a comment below (at least 1-2 sentences) to gain an entry into the giveaway.
We'll randomly pick 30 entries to win a BlizzCon Virtual Ticket. This is a very short giveaway, to ensure we have enough time to pick winners before BlizzCon actually starts. Note: this giveaway has ended. The winners are: proudtiago, Firstmate, xbridgex, bstarss, Gyousa, Thedrawings, ED209, SuBw00FeR, Bujbonel, SirTurbek, SwifttheWild, deadwalker42, Steelwar, JORGEKOBO, Ploratio, burninice, Tyrux, RetPally72, belleteyn, Kharneus, Mostvp71, paradidlle, Byrhtnoth, nahado73, Sunetra, Whisperwood90, Crawclaw, Silmarieni, Madriel, and 420Kid.
Suggestion More gender choices coming. Ptr Client nicht instalierbar Best WoW Joke: Go New Player - Levelling LF Reroll How do I contact a GM in game.
WoW Economy Weekly Wrap-Up: Winter Veil, Gold Progression, Auction House Bugs, Inflation Allied Races Character Customization Now Available in Wowhead's Modelviewer "Save Hati" Campaign Created on the Official Forums Celestalon Announces He's Moving to Hearthstone Mythic Antorus Race - Day 3 Recap: Aggramar NA First, Coven of Shivarra Kill Videos The Whispers of Xal'atath - Antorus the Burning Throne Class and Gear Guides Updated for Antorus Patch 7. Please log in, or sign up for a new account and purchase a subscription to continue reading.
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On your next view you will be asked to log in to your subscriber account or create an account and subscribepurchase a subscription to continue reading. In our Declaration of Independence, the founders claim the right to form our own government because it became "necessary for one people to dissolve the political bands" that tie them to another.
Eagar Fire Chief Howard Carlson is interviewed by reporter Trisha Hendricks of Channel 12 News in Phoenix at the Arizona Wildfire Forum April 18. EAGAR State Forester Scott Hunt co-hosted the Arizona Wildfire Forum on April 18 in Eagar along with the Arizona State Forestry Division, the Arizona Insurance Council and the Arizona Forest Health Council.If you do not specify any input fields, all the preferred input fields in the dataset will be included, and if you do not specify an objective field, the last field in your dataset will be considered the objective field.
Note that when gradient boosting option is applied to classification models, the actual number of models created will be a product of the number of classes (categories) and the iterations. For example, if you set boosting iterations to 12 and the number of classes is 3, then the number of models created will be 36 or less depending on whether an early stopping strategy is used or not. Individual trees in the boosted trees differ from trees in bagged or random forest ensembles.
Primarily the difference is that boosted trees do not try to predict the objective field directly. Instead, they try to fit a gradient (correcting for mistakes made in previous iterations), and this will be stored under a new field, named gradient. This means the predictions from boosted trees cannot be combined with using the regular ensemble combiners. Instead, boosted trees use their own combiner that relies on a few new parameters included with individual boosted trees.Astrologie 2020 cancer
These new parameters will be contained in the boosting attribute in each boosted tree, which may contain the following properties. These are sums of the first and second order gradients, and are needed for generating predictions when encountering missing data and using the proportional strategy.
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For regression problems, a prediction is generated by finding the prediction from each individual tree and doing a weighted sum using each tree's weight. Once an ensemble has been successfully created it will have the following properties. Creating a ensemble is a process that can take just a few seconds or a few days depending on the size of the dataset used as input, the number of models, and on the workload of BigML's systems.
The ensemble goes through a number of states until its fully completed. Through the status field in the ensemble you can determine when the ensemble has been fully processed and ready to be used to create predictions.5454 zelzah ave 106
Once you delete an ensemble, it is permanently deleted. If you try to delete an ensemble a second time, or an ensemble that does not exist, you will receive a "404 not found" response. However, if you try to delete an ensemble that is being used at the moment, then BigML. To list all the ensembles, you can use the ensemble base URL. By default, only the 20 most recent ensembles will be returned. You can get your list of ensembles directly in your browser using your own username and API key with the following links.
You can also paginate, filter, and order your ensembles. Logistic Regressions Last Updated: Monday, 2017-10-30 10:31 A logistic regression is a supervised machine learning method for solving classification problems.
You can create a logistic regression selecting which fields from your dataset you want to use as input fields (or predictors) and which categorical field you want to predict, the objective field. Logistic regression seeks to learn the coefficient values b0, b1, b2. Xk must be numeric values. To adapt this model to all the datatypes that BigML supports, we apply the following transformations to the inputs:BigML.Giuntas meat farms commack ny
You can also list all of your logistic regressions. Value is a map between field identifiers and a coding scheme for that field. See the Coding Categorical Fields for more details. If not specified, one numeric variable is created per categorical value, plus one for missing values. This can be used to change the names of the fields in the logistic regression with respect to the original names in the dataset or to tell BigML that certain fields should be preferred.
All the fields in the dataset Specifies the fields to be included as predictors in the logistic regression. If false, these predictors are not created, and rows containing missing numeric values are dropped. Example: false name optional String,default is dataset's name The name you want to give to the new logistic regression. Example: "my new logistic regression" normalize optional Boolean,default is false Whether to normalize feature vectors in training and predicting.
The type of the field must be categorical.
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